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Helping Different Companies With Information Management

Enterprise Readiness of Cloud MLOps: Azure Machine Learning, Amazon SageMaker, and Google Vertex AI

May 12, 2022

MLOps is essential for scaling ML. Without it, enterprises risk struggling with costly overhead and stalled progress. Several vendors support MLOps: the major offerings are Microsoft Azure ML, Google Vertex AI, and Amazon SageMaker. We looked at these offerings from the perspective of enterprise features and time to value.

For the analysis, we used categories of time to value and enterprise capabilities. As shown in Table 1, our assessment resulted in a score of 2.95 (out of 3) for Azure ML using managed endpoints, 2.12 for Google Vertex AI, and 2.83 for Amazon SageMaker. The higher the score, the better, and the scoring rubric and methodology are detailed in an appendix to this report.

Get the report here.

The Time for Cloud Master Data Management is Now

May 12, 2022

The demand for data to power cloud apps, improve AI models and deliver on digital business initiatives has never been greater. Cloud MDM can help deliver the trusted business analytics and insights, faster innovation, and improved customer relationship management your company needs to stay competitive.

Get the report here.

SQL Transaction Processing and Analytic Performance Price-Performance Testing

May 7, 2022

This report outlines the results from two GigaOm Field Tests (one transactional and the other analytic) derived from the industry-standard TPC Benchmark™ E (TPC-E) and TPC Benchmark™ H (TPC-H) to compare two IaaS cloud database offerings:

  1. Microsoft SQL Server on Amazon Web Services (AWS) Elastic Cloud Compute (EC2) instances.
  2. Microsoft SQL Server Microsoft on Azure Virtual Machines (VM).

Get the report here.

Cloud Database Performance – McKnight Benchmark Report

March 23, 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.

Get the report here.

Healthcare Natural Language Processing

March 23, 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).

Get the report here.

NetApp Cloud Insights

March 23, 2022

This report format incorporates a field test/benchmark with a white paper-level paper. The body of the paper provides only a summary of testing/results, with the bulk of the process/findings moved to an annex. It therefore makes for a highly readable, punchy, yet detailed paper.

The goal of our study presented in this paper is to objectively uncover whether NetApp is truly positioned to deliver on value propositions to the enterprise. To meet this objective, we designed a field test derived from monitoring, troubleshooting, optimizing, and securing scenarios common to the modern enterprise with, or in the process of, migrating to a hybrid cloud.

This test measured enterprise response to usual and important situations including greedy/degraded applications, underutilized infrastructure, and ransomware simulations.

Get the report here (GigaOm wall).

API and Microservices Management Benchmark

March 23, 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.

Get the report here (GigaOm wall).

Yellowbrick Data

January 31, 2022

The purpose of this Solution Spotlight is to extend the analysis from prior reports into more detail on several of the key criteria and evaluation metrics and further demonstrate Yellowbrick’s status as a Leader and potential as an Outperformer in the rapidly growing and competitive data warehouse space.

Get the report here.

High Performance Application Security Testing

December 9, 2021

In this report, we performance tested security mechanisms on NGINX, AWS, and Azure: ModSecurityNGINX App Protect WAFAWS Web Application Firewall (WAF), and Azure WAF. This last product was tested as a fully managed security offering.

Get the report here.

RADAR for Master Data Management

October 16, 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.

Get the report here.