ABAC vs RBAC: The Advantage of Attribute-Based Access Control over Role-Based Access Control
GigaOm
January 01, 2023
Data security has become an undeniable part of the technology stack for modern applications. No longer an afterthought, protecting application assets—namely data—against cybercriminal activities, insider threats, and basic human negligence needs to happen early and often during the application development cycle and beyond. This benchmark report captures the number of policy changes required to manage ever-evolving data security policies seen in a modern data-driven enterprise. The more policy changes required, the more likely a required change will not take place or an error is made when implementing the change. With this study, we show the impacts of data security governance policy management.
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Tags: Big Data, Cloud, Data Center
CrowdStrike Falcon LogScale Benchmark Report: Log Management and Analytics Platform
GigaOm
January 01, 2023
Real-time observability and enterprise systems monitoring have become critical functions in information technology organizations globally. As organizations continue to digitize and automate key functions, they are introducing more complex systems, hypervisors, virtual machines, Kubernetes, devices, and applications—all of which are generating more log and event data. While the amount of usable log data is growing, there is not an attendant growth in the tools, skilled professionals, and other resources to capture, manage, and analyze this complexity.
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Tags: Big Data, Cloud, Data Center
Confluent Cloud: Fully Managed Kafka Streaming, An Ease-of-Use Comparison
GigaOm
December 13, 2022
This report focuses on real-time data and how autonomous systems can be fed at scale reliably. To shed light on this challenge, we assess the ease of use of a fully managed Kafka platform—Confluent Cloud—and a self-managed open-source Apache Kafka solution.
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Tags: Big Data, Cloud, Data Center
Cloud Parallel File Systems
GigaOm
December 13, 2022
We benchmarked the usability, effort, and performance of the WEKA Data Platform against Amazon FSx for Lustre on AWS. In this hands-on benchmark, we found that WEKA provided comparable or superior usability and outperformed FSx for Lustre at similar capacities by up to 300% or more. On some of our tests, WekaFS IO latency was less than 30% that of FSx for Lustre. Our usability tests also found WEKA to be a mature and easily deployed and operated solution in AWS specifically.
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Tags: Big Data, Cloud, Data Center
Dealing with Data System Complexity in Your Applications
GigaOm
December 13, 2022
In conventional information architectures, enterprise needs requires two different database technologies: online transactional processing (OLTP) database management systems (DBMS) to handle transactional workloads and online analytical processing (OLAP) DBMS to perform analytics and reporting. Data types also drive multiple technologies since many databases specialize in types like time series, geospatial, graph, JSON, etc. If there is a single database that can be used to avoid the overhead, it is worthwhile to look into that database for complete application management.
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Tags: Big Data, Cloud, Data Center
Advantages of DataStax Astra Streaming for JMS Applications
GigaOm
December 13, 2022
Competitive markets demand rapid, well-informed decision-making to succeed. In response, enterprises are building fast and scalable data infrastructures to fuel time-sensitive decisions, provide rich customer experiences enable better business efficiencies, and gain a competitive edge. In our comparative study, we used the Starlight for JMS feature included in DataStax Astra Streaming along with self-managed open-source Apache ActiveMQ Artemis JMS instances. We found several notable differences and benefits for modernizing a JMS-based data streaming stack.
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Tags: Big Data, Cloud, Data Center
API and Microservices Management Benchmark: Product Evaluation: Kong Enterprise, Apigee X and MuleSoft Anypoint
GigaOm
December 13, 2022
Application programming interfaces, or APIs, are a ubiquitous method and de facto standard of communication among modern information technologies. The information ecosystems within large companies and complex organizations encompass a vast array of applications and systems, many of which have turned to APIs for exchanging data as the glue that holds these heterogeneous artifacts together. APIs have begun to replace older, more cumbersome methods of information sharing with lightweight, loosely-coupled microservices. This change allows organizations to knit together disparate systems and applications without creating technical debt from tight coupling with custom code or proprietary, unwieldy vendor tools.
This report reveals the results of performance testing we completed on these API and microservices management platforms: Kong Enterprise, Google Cloud Apigee X, and MuleSoft Anypoint Flex Gateway.
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Tags: Big Data, Cloud, Data Center
Transactional and Analytical Workloads: How Transactional and Analytical Performance Impacts the TCO of Cloud Databases
GigaOm
December 13, 2022
Competitive data-driven organizations rely on data-intensive applications to win in the digital service economy. These applications require a robust data tier that can handle the diverse workloads demands of both transactional and analytical processing while serving an interactive, immersive customer experience. The resulting database workloads demand low-latency responses, fast streaming data ingestion, complex analytic queries, high concurrency, and large data volumes.
This report outlines the results from a Field Test derived from three industry standard benchmarks—TPC Benchmark H (TPC-H), TPC Benchmark DS (TPC-DS), and TPC Benchmark C (TPC-C)—to compare SingleStoreDB, Amazon Redshift, and Snowflake.
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Tags: Big Data, Cloud, Data Center
Cloud Analytics Platform Total Cost of Ownership v2.0
GigaOm
December 02, 2022
Organizations today need a broad set of enterprise data cloud services with key data functionality to modernize applications and utilize machine learning. We decided to take four leading platforms for machine learning under analysis. We have learned that the cloud analytic framework selected for an enterprise and an enterprise project matters in terms of cost.
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Tags: Big Data, Cloud, Data Center
Log and Telemetry Analytics Performance Benchmark
GigaOm
December 01, 2022
This report focuses on the performance of cloud-enabled, enterprise-ready, popular log analytical platforms Microsoft Azure Data Explorer (part of Azure Synapse Analytics), Google BigQuery, and Snowflake. Due to cost limitations with Elasticsearch and AWS OpenSearch, we could not run our tests on Elasticsearch. Microsoft invited GigaOm to measure the performance of the Azure Data Explorer engine and compare it with its leading competitors in the log analytics space. The tests we designed intend to simulate a set of basic scenarios to answer fundamental business questions that an organization from nearly any industry might encounter in their log analytics.
In this report, we tested complex workloads with a volume of 100TB of data and concurrency of 1 and 50 concurrent users. The testing was conducted using comparable hardware configurations on Microsoft Azure and Google Cloud.
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Tags: Big Data, Cloud, Data Center
Managing Microsoft Azure Arc-Enabled Infrastructure from the Azure Portal
GigaOm
December 01, 2022
An Azure Arc-enabled infrastructure is a cloud infrastructure that is managed and monitored by Microsoft Azure. It includes features such as Azure Resource Manager, Azure Monitor, and Azure Security Center. The Azure portal is a web-based management tool that provides a unified experience for managing all Azure resources. The Azure portal allows you to create, manage, and monitor Azure resources in a single, unified console. Many are managing their Microsoft Azure Arc-enabled infrastructure from an Azure portal.
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Tags: Big Data, Cloud, Data Center
High-Performance Web Application Firewall Testing
GigaOm
December 01, 2022
This report focuses on web application security mechanisms deployed in the cloud and closer to your apps. The cloud enables enterprises to rapidly differentiate and innovate with microservices and allows microservice endpoints to be cloned and scaled in a matter of minutes. It reviews F5 NGINX App Protect WAF vs. AWS WAF, Azure Web Application Firewall, and Cloudflare WAF.
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Tags: Big Data, Cloud, Data Center
The Data Warehouse in Multi-Cloud and Hybrid Cloud
GigaOm
December 01, 2022
Your Analytical Database Deployment will probably be to Multiple Clouds. Learn about the Role of the Data Warehouse in a World with Data Lakes, Data Science and Decentralization, Options for Provisioning the Data Warehouse and Why Multiple Clouds, Cloudwashing – Cloud-Enabled/Hosted vs Cloud-Native vs Cloud-Owned and Multi-Cloud Flexibility and Deployment Freedom.
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Tags: Big Data, Cloud, Data Center
API and Microservices Management Benchmark
GigaOm
July 05, 2022
Application programming interfaces, or APIs, are a ubiquitous method and de facto standard of communication among modern information technologies. The information ecosystems within large companies and complex organizations encompass a vast array of applications and systems, many of which have turned to APIs for exchanging data as the glue that holds these heterogeneous artifacts together. APIs have begun to replace older, more cumbersome methods of information sharing with lightweight, loosely-coupled microservices.
In this report, we reveal the results of performance testing we completed on two API and Microservices Management platforms: Kong Enterprise and Google Cloud Apigee X.
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Tags: Big Data, Cloud, Data Center
Healthcare Natural Language Processing
GigaOm
June 22, 2022
Our study examined three public cloud service offerings that use natural language processing to meet the challenge—Google Cloud Healthcare API, Amazon Comprehend Medical, and Microsoft Azure Text Analytics for Health. We manually annotated medical notes to identify terms within the documents from a common set of entities and relationships. Next, we built an annotation taxonomy by comparing the taxonomies of the three NLP solutions and created a standard mapping of the entities and relationships shared by all three platforms. We then compared our annotations to the annotations of each solution, using the annotation taxonomy, and noted false negatives (not desired), true positives (desired), and false positives (not desired).
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Tags: Big Data, Cloud, Data Center
Cloud Database Performance – McKnight Benchmark Report
Vertica
June 15, 2022
A report by McKnight Consulting Group used industry-standard benchmarks to test three well-known, cloud-optimized analytical platforms – Vertica in Eon Mode, Amazon Redshift, and Snowflake.
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Tags: Big Data, Cloud, Data Center
SECTOR ROADMAP: MODERN ENTERPRISE GRADE DATA INTEGRATION
GigaOm
June 15, 2022
This Sector Roadmap is focused on data integration (DI) selection for multiple/general purposes across the enterprise.
Vendor solutions are evaluated over six Disruption Vectors: SaaS Applications Connectivity, Use of Artificial Intelligence, Conversion from any format to any format, Intuitive and Programming Time Efficient, Strength in DevOps and Shared Metadata across data platforms.
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Tags: Big Data, Cloud, Data Center
CASSANDRA TOTAL COST OF OWNERSHIP STUDY
GigaOm
April 06, 2022
This study examines the full cost and true value of Cassandra self-managed on Google Cloud (GCP) and the cost of a fully managed serverless Cassandra service. We included dedicated compute hardware (for self-managed Cassandra), cost per read and write operation (on serverless Cassandra), storage growth (each write operation adds new data) and people cost in our three-year total cost of ownership calculations. People costs take into account that certain capabilities in serverless Cassandra needed for the workload were not available in self-managed Cassandra, requiring workarounds. We used market rates and typical splits of full-time equivalent (FTE) and consulting to determine our people costs.
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Tags: Big Data, Cloud, Data Center
Enterprise Analytic Solutions 2021
GigaOm
December 03, 2021
In this paper, we focus on the higher-volume, critical-app compute and storage that is the analytic database. We have undertaken the ambitious goal of evaluating the current vendor landscape and assessing the analytic platforms that have made, or are in the process of making, the leap to a new generation of capabilities in order to support the AI-based enterprise.
For this Roadmap Report, we chose technologies powered for an enterprise-class application in a midsize to large enterprise. We considered popularity and interest. The vendors/products chosen were:
Actian Avalanche
Amazon Redshift
Cloudera Data Platform
Google BigQuery
IBM Db2 Warehouse on Cloud and Cloud Pak for Data
Microsoft Azure Synapse Analytics
Oracle Autonomous Data Warehouse
Snowflake
Teradata Vantage
Vertica
Yellowbrick
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Tags: Big Data, Cloud, Data Center
RADAR for Master Data Management
GigaOm
December 03, 2021
The economic payback of master data management starts with “build once, use often.” Master data must be accessible to each new application that is built, and these applications routinely have up to 50% effort and budget directed toward collecting master data.
This GigaOm Radar report evaluates the capabilities of notable players in the MDM space against the decision-making framework established in the Key Criteria Report for Master Data Management.
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Tags: Big Data, Cloud, Data Center
SQL TRANSACTION PROCESSING, PRICE-PERFORMANCE TESTING, MICROSOFT SQL SERVER EVALUATION: AZURE VIRTUAL MACHINES VS. AMAZON WEB SERVICES EC2
GigaOm
November 22, 2021
This report outlines the results from a GigaOm Transactional Field Test, derived from the industry-standard TPC Benchmark E (TPC-E), to compare two IaaS cloud database offerings:
Microsoft SQL Server on Amazon Web Services (AWS) Elastic Cloud Compute (EC2) instances
Microsoft SQL Server on Microsoft Azure Virtual Machines (VM)
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Tags: Big Data, Cloud, Data Center
CLOUD DATA SECURITY COMPARISON: IMMUTA AND APACHE RANGER
GigaOm
November 21, 2021
Data security has become an immutable part of the technology stack for modern applications. Protecting application assets and data against cybercriminal activities, insider threats, and basic human negligence is no longer an afterthought. It must be addressed early and often, both in the application development cycle and the data analytics stack.
To measure the policy management burden, we designed a reproducible test that included a standardized, publicly available dataset and a number of access control policy management scenarios based on real world use cases we have observed for cloud data workloads. We tested two options: Apache Ranger with Apache Atlas and Immuta.
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Tags: Big Data, Cloud, Data Center
Choosing the Right Data Warehouse-as-a-Service for Your Analytical Needs
MCG
November 16, 2021
This paper examines the different flavors of DWaaS to ensure you get into the right one. Then it looks at some of the key criteria that should be considered when reviewing the cloud database.
Behind the covers of the DWaaS term, there are three distinct approaches. While all include most of the benefits for DWaaS, the differences mean that the benefits will accrue quite differently according to the fit of the model to the enterprise. These are vast enough differences to actually be the deciding factor in the DWaaS selection.
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Tags: Big Data, Cloud, Data Center
Embedded Database Performance Report
MCG
November 10, 2021
This benchmark compared Actian Zen Enterprise Server and MySQL Enterprise, both running on the same Ubuntu Linux in 8- and 16-core VMs as AWS EC2 instances, each using its ODBC driver. The benchmark used is derived from the TPC-C industry standard benchmark.
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Tags: Big Data, Cloud, Data Center
SQL TRANSACTION PROCESSING, PRICE-PERFORMANCE TESTING, MICROSOFT SQL SERVER EVALUATION: AZURE VIRTUAL MACHINES VS. AMAZON WEB SERVICES EC2
GigaOm
October 20, 2021
This report outlines the results from a GigaOm Transactional Field Test, derived from the industry-standard TPC Benchmark E (TPC-E), to compare two IaaS cloud database offerings:
Microsoft SQL Server on Amazon Web Services (AWS) Elastic Cloud Compute (EC2) instances
Microsoft SQL Server on Microsoft Azure Virtual Machines (VM)
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Tags: Big Data, Cloud, Data Center
ENTERPRISE READINESS OF CLOUD MLOPS
GigaOm
October 14, 2021
MLOps is essential for scaling ML. Without it, enterprises risk struggling with costly overhead and stalled progress. Several vendors have emerged with offerings to support MLOps: the major offerings are Microsoft Azure ML and Google Vertex AI. We looked at these offerings from the perspective of enterprise features and time-to-value.
For the analysis, we used categories of Total Cost of Ownership (TCO) time-to-value and enterprise capabilities. Our assessment resulted in a score of 2.9 (out of 3) for Azure ML using managed endpoints, 1.9 for Google Vertex AI, and TK for AWS SageMaker. The assessment and scoring rubric and methodology are detailed in an annex to this report.
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Tags: Big Data, Cloud, Data Center
CLOUD DATA SECURITY COMPARISON: IMMUTA AND APACHE RANGER
GigaOm
October 13, 2021
Data security has become an immutable part of the technology stack for modern applications. Protecting application assets and data against cybercriminal activities, insider threats, and basic human negligence is no longer an afterthought. It must be addressed early and often, both in the application development cycle and the data analytics stack.
To measure the policy management burden, we designed a reproducible test that included a standardized, publicly available dataset and a number of access control policy management scenarios based on real world use cases we have observed for cloud data workloads. We tested two options: Apache Ranger with Apache Atlas and Immuta.
See publication
Tags: Big Data, Cloud, Data Center
Embedded Database Performance Report
MCG
October 13, 2021
This benchmark compared Actian Zen Enterprise Server and MySQL Enterprise, both running on the same Ubuntu Linux in 8- and 16-core VMs as AWS EC2 instances, each using its ODBC driver. The benchmark used is derived from the TPC-C industry standard benchmark.
See publication
Tags: Big Data, Cloud, Data Center
Choosing the Right Data Warehouse-as-a-Service for Your Analytical Needs
GigaOm
October 06, 2021
This paper examines the different flavors of DWaaS to ensure you get into the right one. Then it looks at some of the key criteria that should be considered when reviewing the cloud database.
Behind the covers of the DWaaS term, there are three distinct approaches. While all include most of the benefits for DWaaS, the differences mean that the benefits will accrue quite differently according to the fit of the model to the enterprise. These are vast enough differences to actually be the deciding factor in the DWaaS selection.
See publication
Tags: Big Data, Cloud, Data Center
Enterprise Analytic Solutions 2021
GigaOm
October 06, 2021
In this paper, we focus on the higher-volume, critical-app compute and storage that is the analytic database. We have undertaken the ambitious goal of evaluating the current vendor landscape and assessing the analytic platforms that have made, or are in the process of making, the leap to a new generation of capabilities in order to support the AI-based enterprise.
For this Roadmap Report, we chose technologies powered for an enterprise-class application in a midsize to large enterprise. We considered popularity and interest. The vendors/products chosen were:
Actian Avalanche
Amazon Redshift
Cloudera Data Platform
Google BigQuery
IBM Db2 Warehouse on Cloud and Cloud Pak for Data
Microsoft Azure Synapse Analytics
Oracle Autonomous Data Warehouse
Snowflake
Teradata Vantage
Vertica
Yellowbrick
See publication
Tags: Big Data, Cloud, Data Center
ENTERPRISE READINESS OF CLOUD MLOPS
GigaOm
September 01, 2021
MLOps is essential for scaling ML. Without it, enterprises risk struggling with costly overhead and stalled progress. Several vendors have emerged with offerings to support MLOps: the major offerings are Microsoft Azure ML and Google Vertex AI. We looked at these offerings from the perspective of enterprise features and time-to-value.
For the analysis, we used categories of Total Cost of Ownership (TCO) time-to-value and enterprise capabilities. Our assessment resulted in a score of 2.9 (out of 3) for Azure ML using managed endpoints, 1.9 for Google Vertex AI, and TK for AWS SageMaker. The assessment and scoring rubric and methodology are detailed in an annex to this report.
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Tags: Big Data, Cloud, Data Center
CLOUD DATA WAREHOUSE PERFORMANCE TESTING: CLOUDERA DATA WAREHOUSE, AMAZON REDSHIFT, MICROSOFT AZURE SYNAPSE, GOOGLE BIGQUERY, AND SNOWFLAKE
GigaOm
August 10, 2021
This report outlines the results from an analytic performance test derived from the industry-standard TPC Benchmark DS (TPC-DS) to compare Cloudera Data Warehouse service (CDW)—part of the broader Cloudera Data Platform (CDP)—with four prominent competitors: Amazon Redshift, Azure Synapse Analytics, Google BigQuery, and Snowflake. Overall, the test results were insightful in revealing query execution performance of these platforms.
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Tags: Big Data, Cloud, Data Center
KEY CRITERIA FOR EVALUATING MASTER DATA MANAGEMENT
GigaOm
August 09, 2021
An Evaluation Guide for Technology Decision Makers.
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Tags: Big Data, Cloud, Data Center
BENCHMARK REPORT: TRILLION EDGE KNOWLEDGE GRAPH
MCG
July 06, 2021
Our latest benchmark report, Trillion Edge Knowledge Graph, is the first demonstration of a massive knowledge graph that consists of materialized data and Virtual Graphs spanning hybrid multicloud data sources.
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Tags: Big Data, Cloud, Data Center
Extra Credit v MongoDB: How the U.K.’s Department of Work and Pensions Scaled Universal Credit to Meet the COVID-19 Crisis
GigaOm
June 10, 2021
The COVID-19 pandemic and subsequent shutdowns posed a direct and unique challenge to the United Kingdom’s Department for Work and Pensions, as the number of active claimants spiked from more than 2 million just before the pandemic to more than 5 million in the span of a couple months. Learn how the DPW leveraged MongoDB to scale its microservices-based infrastructure to protect millions of citizens during a time of crisis.
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Tags: Big Data, Cloud, Data Center
Cloud Analytics Platform Total Cost of Ownership
GigaOm
June 10, 2021
Organizations today need a broad set of enterprise data cloud services with key data functionality to modernize applications and utilize machine learning. They need a platform designed to address multi-faceted needs by offering multi-function data management and analytics to solve the enterprise’s most pressing data and analytic challenges in a streamlined fashion. They need a selection that allows a worry-less experience with the architecture and its components.
We decided to take four leading platforms – Azure, AWS, GCP and Snowflake – for machine learning under analysis. We have learned that the cloud analytic framework selected for an enterprise, and for an enterprise project, matters to cost.
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Tags: Big Data, Cloud, Data Center
A Report on the Cost Savings of Replacing Kafka with Pulsar
GigaOm
June 02, 2021
Picking the wrong event streaming platform for your organization can have massive consequences in terms of fit, function and of course cost. With Apache Pulsar quickly gaining mindshare within enterprises that need a comprehensive, open source event streaming and messaging platform, the expert researchers at GigaOm decided to see how this new, up and coming technology compares to the old industry stalwart: Apache Kafka.
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Tags: Big Data, Cloud, Data Center
HIGH PERFORMANCE API MANAGEMENT TESTING: PRODUCT EVALUATION: API7 AND KONG ENTERPRISE
GigaOm
May 12, 2021
This report focuses on API management platforms deployed in the cloud. The cloud enables enterprises to differentiate and innovate with microservices at a rapid pace. It allows API endpoints to be cloned and scaled in a matter of minutes. And it offers elastic scalability compared with on-premises deployments, enabling faster server deployment and application development, and allowing less costly compute.
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Tags: Big Data, Cloud, Data Center
SQL TRANSACTION PROCESSING, PRICE-PERFORMANCE TESTING: MICROSOFT SQL SERVER EVALUATION: AZURE VIRTUAL MACHINES VS. AMAZON WEB SERVICES EC2
GigaOm
March 01, 2021
This report outlines the results from a GigaOm Transactional Field Test, derived from the industry-standard TPC Benchmark E (TPC-E), to compare two IaaS cloud database offerings:
Microsoft SQL Server on Amazon Web Services (AWS) Elastic Cloud Compute (EC2) instances
Microsoft SQL Server Microsoft on Azure Virtual Machines (VM)
Both are installations of Microsoft SQL Server, and we tested Red Hat Enterprise Linux OS.
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Tags: Analytics, Big Data, Cloud
Designing Data: How a Pharmacy Benefit Management Firm Modernized its Data Architecture Around Microservices and Real-Time Integration
GigaOm
February 02, 2021
Our use case describes a pharmacy benefit manager (PBM) company that processes and pays prescription drug claims for its members. The company contracts with pharmacies and builds and maintains drug formularies. It also negotiates discounts and rebates with drug manufacturers, providing cost-effective prescription drug benefits for its clients and their members.
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Tags: Analytics, Big Data, Data Center
Modernize Data Warehousing: Beyond Performance, The Importance of Other Key Attributes
Vertica
February 02, 2021
Organizations looking for enterprise data warehouses (EDWs) cannot afford to base their evaluation on query price-performance alone. There’s much more to it. You also need capabilities that reduce the time needed for configuration, management, tuning, and other tasks that can take away from valuable time spent on business analytics.
This new whitepaper from McKnight Consulting Group explores factors that can reduce the costs of analytics far beyond performance, such as licensing structure, data storage, support for non-structured data, concurrency scaling, and much more. Download your copy today, and make a well-informed decision when choosing an EDW platform.
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Tags: Big Data, Cloud, Data Center
BENCHMARK REPORT: CONTAINERIZED SQL SERVER PERFORMANCE TESTING
GigaOm
January 13, 2021
We conducted an unbiased benchmark study of SQL Server 2019 running on the most promising Kubernetes platforms available on the market today. Our goal is to help each customer determine the best-suited platform to run Microsoft SQL Server based on their individual requirements.
Read the full benchmark report, which provides insight to help IT professionals, DevOps engineers, platform architects and information security practitioners evaluate a Kubernetes platform optimal for running I/O intensive Microsoft SQL Server applications.
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Tags: Big Data, Cloud, Data Center, DevOps
CLOUD DATA WAREHOUSE PERFORMANCE TESTING
MCG
January 11, 2021
This report focuses on relational analytical databases in the cloud, because deployments are at an all-time high and poised to expand dramatically. This report outlines the results from a field test derived from the industry standard TPC Benchmark DS (TPC-DS) comparing five relational analytical databases based on scale-out cloud data warehouses.
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Tags: Big Data, Cloud
MOVING THE ENTERPRISE ANALYTICAL DATABASE – A GUIDE FOR ENTERPRISES: STRATEGIES AND OPTIONS TO MODERNIZING DATA ARCHITECTURE AND THE DATA WAREHOUSE
GigaOm
January 01, 2021
The benefits of modern data architecture are as follows:
It ensures the ability of the data analysis function of the organization to actually do analysis rather than restrict it to data hunting and preparation almost exclusively.
It provides the ability to maneuver as an organization in the modern era of information competition with consistent, connected data sets with every data set playing a mindful and appropriate role.
It enables a company to measure and improve the business with timely key performance indicators, such as streamlining your supply chain or opening up new markets with new products and services supported by technology built for analytics.
This paper will help an organization understand the value of modernizing its data architecture and how to frame a modernization effort that delivers analysis capabilities, diverse yet connected data, and key performance measures.
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Tags: Big Data, Cloud, Data Center
SQL TRANSACTION PROCESSING PRICE-PERFORMANCE TESTING: AZURE VIRTUAL MACHINES VS. AWS EC2 INSTANCES
GigaOm
November 11, 2020
Get free access to this 30-page GigaOm Transactional Field Test, derived from the industry-standard TPC Benchmark E (TPC-E), to compare two IaaS cloud database offerings: Microsoft SQL Server on Amazon Web Services (AWS) Elastic Compute Cloud (EC2) instances; Microsoft SQL Server Microsoft on Azure Virtual Machines (VM). Both are installations of Microsoft SQL Server and we tested on both Windows Server OS and Red Hat Enterprise Linux OS.
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Tags: Big Data, Cloud, Data Center
APPLICATION CACHE PERFORMANCE PRODUCT EVALUATION: AZURE CACHE FOR REDIS
GigaOm
September 07, 2020
Applications and their performance requirements have evolved dramatically in today’s landscape. The cloud enables enterprises to differentiate and innovate with APIs and microservices at a rapid pace. Cloud providers, like Azure, allow microservice endpoints to be cloned and scaled in a matter of minutes. The cloud offers elastic scalability compared to on-premises deployments, enabling faster server deployment and application development and less costly compute. In this paper, we reveal the results of application performance testing we completed both with and without Azure Cache for Redis on top of Azure SQL Database and Azure Database for PostgreSQL.
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Tags: Big Data, Cloud, Data Center
MCG ENTERPRISE CONTRIBUTION RANKING REPORT FOR CLOUD DATA MANAGEMENT AND INTEGRATION FOR CLOUD DATA WAREHOUSES AND DATA LAKES
MCG
August 05, 2020
In this paper, we have undertaken an ambitious goal of evaluating the current vendor landscape and assessing which tools and platforms have made, or are in the process of making, the leap to this new generation of data management and integration capabilities.
The vendors/products chosen were:
AWS (Glue)
Azure (Azure Data Factory)
Cloudera (Cloudera Replication Manager)
Fivetran
Google (Alooma)
IBM
Informatica
Matillion
Oracle
SAP
Talend
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Tags: Big Data, Cloud, Data Center
CLOUD DATA WAREHOUSE PERFORMANCE TESTING
GigaOm
August 05, 2020
This report focuses on relational analytical databases in the cloud, because deployments are at an all-time high and poised to expand dramatically. This report outlines the results from a field test derived from the industry standard TPC Benchmark DS (TPC-DS) comparing five relational analytical databases based on scale-out cloud data warehouses.
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Tags: Big Data, Cloud, Data Center
EMPOWERING USERS TO MINE THE DATA LAKE, ENERGIZE A DATA CATALOG AND RETURN BIG ROI
GigaOm
July 14, 2020
In this Business Technology Impact report, we take a look at a large multi-national firm and its implementation of a data lake and data catalog. Within the company, a small team worked to transform the data lake from an underutilized, misunderstood ‘white elephant’ into a resource that drove the company’s growth and innovation.
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Tags: Big Data, Cloud, Data Center
HIGH PERFORMANCE APPLICATION SECURITY TESTING, PRODUCT EVALUATION: NGINX APP PROTECT VS. MODSECURITY (PLUS AWS WEB Application)
GigaOm
July 13, 2020
Data, web, and application security has evolved dramatically over the past few years. Just as new threats abound, the architecture of applications—how we build and deploy them—has changed. We’ve traded monolithic applications for microservices running in containers and communicating via application programming interfaces (APIs)—and all of it deployed through automated continuous integration/continuous deployment (CI/CD) pipelines. The frameworks we have established to build and deploy applications are optimized for time to market—yet security remains of utmost importance.
Our focus is specifically on approaches to securing apps, APIs, and microservices that are tuned for high performance and availability. We define “high performance” as companies that experience workloads of more than 1,000 transactions per second (tps) and require a maximum latency below 30 milliseconds across the landscape.
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Tags: Big Data, Cloud, Data Center
API AND MICROSERVICES MANAGEMENT PRODUCT EVALUATION: KONG ENTERPRISE, APIGEE EDGE, AND APIGEE EDGE MICROGATEWAY
GigaOm
July 07, 2020
Application programming interfaces, or APIs, are now a ubiquitous method and de facto standard of communication among modern information technologies. The information ecosystems within large companies and complex organizations comprise a vast array of applications and systems, many of which have turned to APIs to exchange data as the glue to hold these heterogeneous artifacts together. In this paper, we reveal the results of performance testing we completed across three API and Microservices Management platforms: Kong Enterprise, Apigee Edge, and Apigee Edge Microgateway.
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Tags: Big Data, Cloud, Data Center
HIGH PERFORMANCE CLOUD DATA WAREHOUSE VENDOR EVALUATION
GigaOm
June 16, 2020
This authoritative report from GigaOm Research, a respected independent industry analyst firm, details the key performance and cost criteria to guide your cloud data warehouse selection.
“Price and performance are critical points of interest…our analysis reveals Avalanche to be the industry leader on this criterion.”
Highlights from the report:
Key factors to consider when evaluating a hybrid cloud data warehouse
Head-on vendor comparisons across performance and cost using industry standard TPC-H benchmark
Vendors analyzed include Actian Avalanche, Snowflake, Amazon Redshift, Microsoft Azure Synapse and Google BigQuery
Assessment of single user and multiple concurrent users scenarios
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Tags: Big Data, Cloud, Data Center
TRANSITIONING FROM POSTGRESQL TO AN ANALYTICAL DATABASE FOR HIGHER PERFORMANCE AND MASSIVE SCALE
Vertica
June 15, 2020
In today’s data driven world, where effective decisions are based on a company’s ability to access information in seconds or minutes rather than hours or days, selecting the right analytical database platform is critical.
Read this McKnight white paper to learn:
Which criteria to consider for an analytical database
The process for transitioning away from PostgreSQL
Transition success stories from Etsy, TravelBird and Nimble Storage
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Tags: Big Data, Cloud, Data Center
DATA PIPELINE PLATFORM COMPARISON
GigaOm
June 08, 2020
In this report, we compare the three major data pipeline platforms: Matillion, Stitch, and Fivetran; and run them through a series of selected tests that highlight their degree of automation, ease of setup, and documentation. We evaluated aspects that include the time and effort required to set up a source-destination connection, the degree of automation throughout the process, and the quality of documentation to support the effort. These areas address the three major “humps of work” we have encountered in our field work with data pipelines.
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Tags: Big Data, Cloud, Data Center
DATA PIPELINE PLATFORM COMPARISON
GigaOm
April 20, 2020
In this report, we compare the three major data pipeline platforms: Matillion, Stitch, and Fivetran; and run them through a series of selected tests that highlight their degree of automation, ease of setup, and documentation. We evaluated aspects that include the time and effort required to set up a source-destination connection, the degree of automation throughout the process, and the quality of documentation to support the effort. These areas address the three major “humps of work” we have encountered in our field work with data pipelines.
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Tags: Big Data, Cloud, Data Center
PRICE PERFORMANCE IN MODERN CLOUD DATABASE MANAGEMENT SYSTEMS
Teradata
April 15, 2020
The pace of relational analytical databases deploying in the cloud are at an all-time high. The goal of this paper is to provide information to help a customer make the best decision, looking at factors in cloud data platform pricing – such as scope, scale, deployment, etc. – and how to determine the ultimate success metric when it comes to making a decision on a cloud data warehouse deployment – price-performance.
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Tags: Big Data, Cloud, Data Center
CLOUD DATABASE PERFORMANCE – MCKNIGHT BENCHMARK REPORT
MCG
April 13, 2020
This third-party report from McKnight Consulting Group uses industry-standard benchmark principles to evaluate the performance of three cloud-optimized analytical platforms architected for the separation of compute and storage – Vertica in Eon Mode, Amazon Redshift, and an unnamed cloud data platform.
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Tags: Big Data, Cloud, Data Center
ENTERPRISE ANALYTIC SOLUTIONS
GigaOm
April 07, 2020
This report is the third in a series of enterprise roadmaps addressing cloud analytic databases. The last two reports focused on comparing vendors on key decision criteria that were targeted primarily at cloud integration. This report is an update to the 2019 Enterprise Roadmap: Cloud Analytic Databases. However, this time around we have new vendors and a new name. We’ve reviewed and adjusted our inclusion criteria. We’re now targeting the technologies that tackle the objectives of an analytics program, as opposed to the means by which they are achieving these objectives.
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Tags: Big Data, Cloud, Data Center
HIGH PERFORMANCE API MANAGEMENT TESTING
GigaOm
March 24, 2020
Application programming interfaces, or APIs, are now a ubiquitous method and de facto standard of communication among modern information technology applications. Large companies and complex organizations have turned to APIs for exchanging data to knit these heterogeneous systems together and turn data into a service. In this paper, we reveal the results of performance testing we completed with four full-lifecycle API management platforms.
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Tags: Big Data, Cloud, Data Center
SQL TRANSACTION PROCESSING, PRICE-PERFORMANCE TESTING
GigaOm
January 13, 2020
This report details the results of a Transactional Field Test, derived from the industry-standard TPC Benchmark E (TPC-E), compared:
Microsoft SQL Server 2019 on an Amazon Web Services (AWS) r5a.8xlarge Elastic Cloud Compute (EC2) instance with General Purpose (gp2) volumes
Microsoft SQL Server 2019 on an Azure E32as_v4 Virtual Machine (VM) with P30 Premium Storage drives
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Tags: Big Data, Cloud, Data Center
BENCHMARKING ENTERPRISE STREAMING DATA AND MESSAGE QUEUING PLATFORMS
GigaOm
January 09, 2020
This category of data is known by several names: streaming, messaging, live feeds, real-time, event-driven, and so on. This type of data needs special attention, because delayed processing can and will negatively affect its value—a sudden price change, a critical threshold met, an anomaly detected, a sensor reading changing rapidly, an outlier in a log file—all can be of immense value to a decision maker, but only if he or she is alerted in time to affect the outcome.
We will introduce and demonstrate a method for an organization to assess and benchmark—for their own current and future uses and workloads—the technologies currently available. We will begin by reviewing the landscape of streaming data and message queueing technology. They are alike in purpose—process massive amounts of streaming data generated from social media, logging systems, clickstreams, Internet-of-Things devices, and so forth. However, they also have a few distinctions, strengths, and weaknesses.
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Tags: Big Data, Cloud, Data Center
DELIVERING ON THE VISION OF MLOPS: A MATURITY-BASED APPROACH
GigaOm
August 13, 2019
This report is targeted at Business and IT decision-makers as they look to implement MLOps, which is an approach to deliver Machine Learning- (ML-) based innovation projects. As well as describing how to address the impact of ML across the development cycle, it presents an approach based on maturity levels such that the organization can build on existing progress.
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Tags: Big Data, Cloud, Data Center
MODERNIZING INSURANCE DATA PLATFORMS TO IMPROVE GOVERNANCE AND ENRICH CUSTOMER EXPERIENCE
GigaOm
June 13, 2019
Pekin Insurance is one of the nation’s most successful insurance providers, with combined assets of $2 billion, more than 800 employees, 1,500 agencies, and 8,500 independent agents. Pekin Insurance is on the fast path to a full overhaul and modernization of their data, from the platform, to quality, to governance, to enabling consumers. They have built a 3-year strategy focusing on Data & Analytics and are wrapping up the final year, focused on a robust data layer with a data lake and a data warehouse, on target, on budget, and within scope.
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Tags: Analytics, Big Data, Cloud
EMBEDDED DATABASE PERFORMANCE REPORT 2
MCG
June 06, 2019
Today, to fully harness data to gain a competitive advantage, embedded databases need a high level of performance to provide real-time processing at scale.
See SQLite, the traditional alternative to the file system approach for embedding data management into edge applications and Actian Zen perform.
See for yourself in this benchmark report by McKnight Consulting Group.
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Tags: Big Data, Cloud, Data Center
DATA WAREHOUSE IN THE CLOUD BENCHMARK PRODUCT PROFILE AND EVALUATION: AMAZON REDSHIFT, MICROSOFT AZURE SQL DATA WAREHOUSE, GOOGLE BIGQUERY, AND SNOWFLAKE DATA WAREHOUSE
GigaOm
April 22, 2019
This report outlines the results from the GigaOm Analytic Field Test based on an industry standard TPC Benchmark H (TPC-H)1 to compare Amazon Redshift, Azure SQL Data Warehouse, Google Big Query, and Snowflake Data Warehouse—four relational analytical databases based on scale-out cloud data warehouses and columnar-based database architectures. Despite these similarities, there are some distinct differences in the four platforms.
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Tags: Analytics, Big Data, Cloud
CLOUD DATA WAREHOUSE PERFORMANCE TESTING
GigaOm
April 19, 2019
This report focuses on relational analytical databases in the cloud, because deployments are at an all-time high and poised to expand dramatically. This report outlines the results from a GigaOm Analytic Field Test derived from the industry standard TPC Benchmark DS (TPC-DS)1 comparing Amazon Redshift, Azure SQL Data Warehouse, Google BigQuery, and Snowflake Data Warehouse — four relational analytical databases based on scale-out cloud data warehouses and columnar-based database architectures. Despite these similarities, there are some distinct differences between the four platforms.
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Tags: Big Data, Cloud, Data Center
SQL TRANSACTION PROCESSING, PRICE-PERFORMANCE TESTING ONE
GigaOm
April 17, 2019
This report outlines the results from a Transactional Field Test, derived from the industry-standard TPC Benchmark E (TPC-E), to compare two IaaS cloud database offerings:
Microsoft SQL Server on Amazon Web Services (AWS) Elastic Compute Cloud (EC2) instances
Microsoft SQL Server Microsoft on Azure Virtual Machines (VM)
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Tags: Big Data, Cloud, Data Center
CLOUD DATA WAREHOUSE PERFORMANCE TESTING
GigaOm
April 12, 2019
This report focuses on relational analytical databases in the cloud, because deployments are at an all-time high and poised to expand dramatically. This report outlines the results from a GigaOm Analytic Field Test derived from the industry standard TPC Benchmark DS (TPC-DS)1 comparing Amazon Redshift, Azure SQL Data Warehouse, Google BigQuery, and Snowflake Data Warehouse — four relational analytical databases based on scale-out cloud data warehouses and columnar-based database architectures. Despite these similarities, there are some distinct differences between the four platforms.
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Tags: Big Data, Data Center
CLOUD ANALYTICS PERFORMANCE REPORT
Actian
March 14, 2019
This paper specifically compares two fully-managed, cloud-based analytical databases, Actian Avalanche and Amazon Redshift, two relational analytical databases based on massively parallel processing (MPP) and columnar-based database architectures that scale and provide high-speed analytics. It should be noted while our testing measures the cloud-based performance of both offerings, Avalanche, unlike Redshift, is also available as an on-premise offering, Vector. In addition, Vector is available for developers as a free on-premise community edition, as a download with support in both the Amazon Web Services (AWS) and Azure marketplaces with single-click deployment.
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Tags: Big Data, Cloud, Data Center
MODERNIZING INSURANCE DATA PLATFORMS TO IMPROVE GOVERNANCE AND ENRICH CUSTOMER EXPERIENCE
GigaOm
February 15, 2019
Pekin Insurance is one of the nation’s most successful insurance providers, with combined assets of $2 billion, more than 800 employees, 1,500 agencies, and 8,500 independent agents. Pekin Insurance is on the fast path to a full overhaul and modernization of their data, from the platform, to quality, to governance, to enabling consumers. They have built a 3-year strategy focusing on Data & Analytics and are wrapping up the final year, focused on a robust data layer with a data lake and a data warehouse, on target, on budget, and within scope.
See publication
Tags: Analytics, Big Data, Cloud
CLOUD DATA WAREHOUSE PERFORMANCE TESTING
GigaOm
February 11, 2019
This report focuses on relational analytical databases in the cloud, because deployments are at an all-time high and poised to expand dramatically. This report outlines the results from a GigaOm Analytic Field Test derived from the industry standard TPC Benchmark DS (TPC-DS)1 comparing Amazon Redshift, Azure SQL Data Warehouse, Google BigQuery, and Snowflake Data Warehouse — four relational analytical databases based on scale-out cloud data warehouses and columnar-based database architectures. Despite these similarities, there are some distinct differences between the four platforms.
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Tags: Analytics, Big Data, Cloud
CLOUD ANALYTICS PERFORMANCE REPORT
Actian
February 05, 2019
This paper specifically compares two fully-managed, cloud-based analytical databases, Actian Avalanche and Amazon Redshift, two relational analytical databases based on massively parallel processing (MPP) and columnar-based database architectures that scale and provide high-speed analytics. It should be noted while our testing measures the cloud-based performance of both offerings, Avalanche, unlike Redshift, is also available as an on-premise offering, Vector. In addition, Vector is available for developers as a free on-premise community edition, as a download with support in both the Amazon Web Services (AWS) and Azure marketplaces with single-click deployment.
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Tags: Analytics, Big Data, Cloud
CLOUD ANALYTICS PERFORMANCE REPORT
Actian
January 15, 2019
This paper specifically compares two fully-managed, cloud-based analytical databases, Actian Avalanche and Amazon Redshift, two relational analytical databases based on massively parallel processing (MPP) and columnar-based database architectures that scale and provide high-speed analytics. It should be noted while our testing measures the cloud-based performance of both offerings, Avalanche, unlike Redshift, is also available as an on-premise offering, Vector. In addition, Vector is available for developers as a free on-premise community edition, as a download with support in both the Amazon Web Services (AWS) and Azure marketplaces with single-click deployment.
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Tags: Analytics, Big Data, Cloud
ANALYST REPORT: API MANAGEMENT BENCHMARK REPORT
GigaOm
December 25, 2018
Application programming interfaces, or APIs, are now a ubiquitous method and de facto standard of communication among modern information technologies. The information ecosystems within large companies and complex organizations are a vast array of applications and systems, many of which have turned to APIs as the glue to hold these heterogeneous artifacts together.
This report examines the results of a performance benchmark completed with two popular API management solutions: Kong and Apigee—two full life-cycle API management platforms built with scale-out potential and architectures for large scale, high performance deployments. Despite these similarities, there are some distinct differences in the two platforms.
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Tags: Analytics, Big Data, Cloud
ANALYST REPORT: STATE OF DATA WAREHOUSE
GigaOm
October 25, 2018
Table of Contents
1 The Data Warehouse in the Organization
2 Relationships to Other Research Reports
3 The Data Warehouse Database
4 Analytic Store Platform Choices
5 Choosing the Data Warehouse Platform
6 The Cloud Analytic Database
7 Data Warehouse Flavors
7.1 The Customer Experience Transformation Data Warehouse
7.2 The Asset Maximization with IoT Data Warehouse
7.3 The Operational Extension Data Warehouse
7.4 The Risk Management Data Warehouse
7.5 The Finance Modernization Data Warehouse
7.6 The Product Innovation Data Warehouse
8 Key Takeaways
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Tags: Analytics, Big Data, Cloud
MOVING ANALYTIC WORKLOADS TO THE CLOUD: A TRANSITION GUIDE
GigaOm
June 15, 2018
Recent trends in information management see companies shifting their focus to, or entertaining a notion for a first-time use of, a cloud-based solution for their data warehouse and analytic environment. In the past, the only clear choice for most organizations has been on-premises data solutions —oftentimes using an appliance-based platform. However, the costs of scale are gnawing away at the notion that this remains the best approach for some or all of a company’s analytical needs.
According to market research, through 2020, spending on cloud-based Big Data Analytics technology will grow 4.5x faster than spending for on-premises solutions. Due to the economics and functionality, use of the cloud should now be a given in most database selections. The factors driving data projects to the cloud are many.
Additionally, the multitudinous architectures made possible by hybrid cloud make the question no longer “Cloud, yes or no?” but “How much?” and “How can we get started?” This paper will reflect on the top decision points in determining what depth to move into the cloud and what you need to do in order to be successful in the move. This could be a move of an existing analytical workload or the move of the organization to the cloud for the first time. It’s “everything but the product selection.”
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Tags: Big Data, Cloud, Data Center
EMBEDDED DATABASE PERFORMANCE REPORT 1
MCG
April 12, 2018
This benchmark did a head-to-head comparison of Actian Zen and InfluxDB for IoT time series data, both installed on a Raspberry Pi running Linux ARM/Raspbian using their native APIs (NoSQL).
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Tags: Big Data, Cloud, Data Center
SECTOR ROADMAP: MODERN MASTER DATA MANAGEMENT
GigaOm
June 22, 2017
This Sector Roadmap is focused on master data management (MDM) selection for multiple data domains across the enterprise. In this Sector Roadmap, vendor solutions are evaluated over seven Disruption Vectors: cloud offerings, collaborative data management, going beyond traditional hierarchies, big data integration, machine learning-enabled, APIs and data-as-a-service, and onboard analytics.
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Tags: Big Data, Cloud, Data Center
Yellowbrick Data
High Performance Application Security Testing
Enterprise Analytic Solutions 2021 v4.0
Need a Scale-Out Database?
Integrating Hadoop
Information Management: Strategies for Gaining a Competitive Advantage with Data (The Savvy Manager's Guides)
The Evolution of the Data Platform and What It Means to Data Warehousing
Platforming the Major Analytic Use Cases for Modern Engineering
High Performance Cloud Data Warehouse Vendor Evaluation
