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:
- Microsoft SQL Server on Amazon Web Services (AWS) Elastic Cloud Compute (EC2) instances.
- Microsoft SQL Server Microsoft on Azure Virtual Machines (VM).
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.
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.
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.
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.
In this report, we performance tested security mechanisms on NGINX, AWS, and Azure: ModSecurity, NGINX App Protect WAF, AWS Web Application Firewall (WAF), and Azure WAF. This last product was tested as a fully managed security offering.
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.
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
- Teradata Vantage
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.
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.