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.
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.
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.
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.
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.
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.
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.
This study examines the full cost and true value of self-managed OSS Apache Cassandra® vs DataStax AstraDB fully managed DBaaS in Google Cloud. Our three-year total cost of ownership (TCO) calculations account for dedicated compute hardware (for self-managed Cassandra), cost per read and write operation (on Astra DB), storage growth (each write operation adds new data) and people cost. People costs consider that certain capabilities in Astra DB 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.
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.
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.
Get the report here (wall).