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
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
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
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
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
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)
See publication
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.
See publication
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.
See publication
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.
See publication
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
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
Integrating Hadoop
Information Management: Strategies for Gaining a Competitive Advantage with Data (The Savvy Manager's Guides)
High Performance Cloud Data Warehouse Vendor Evaluation
