ESG Validation

ESG Lab Review: InterSystems IRIS Data Platform: A Unified, Efficient Data Platform for Fast Business Insight

Abstract

This ESG Lab Review documents our audit of InterSystems IRIS Data Platform performance testing. Tests were executed in a proof of concept environment, with comparisons to three common databases. Testing focused on performance of common queries run in the financial services industry.

Topics: Data Platforms, Analytics, & AI

ESG Lab Review: ForeScout Extended Module for Splunk

Abstract

This report provides a first look at the key benefits of ForeScout’s bidirectional integration with Splunk Enterprise and Splunk Enterprise Security (ES), with a focus on how the ForeScout Extended Module can combine ForeScout’s endpoint insight, access control, and automated response capabilities with Splunk’s correlation, analysis, and search features. This integration provides visibility into and control of managed and unmanaged endpoints while helping security teams better understand their security risk posture and respond quickly to mitigate security issues.

Topics: Cybersecurity Data Platforms, Analytics, & AI

ESG Lab Validation: Hitachi Vantara’s Content Platform Portfolio

Introduction

ESG Lab performed hands-on evaluation and testing of the Hitachi Content Platform Portfolio, consisting of the Hitachi Content Platform (HCP), Hitachi Content Platform Anywhere (“HCP Anywhere”) online file sharing, Hitachi Data Ingestor (HDI), and Hitachi Content Intelligence (HCI) data aggregation and analysis. Testing focused on integration of the platforms, global access to content, public and private cloud tiering, data quality and analysis, and the ease of deployment and management of the solution.

Topics: Storage Data Platforms, Analytics, & AI Enterprise Mobility Cloud Services & Orchestration

ESG Lab Review: Conveniently and Securely Archive to Microsoft Azure with HubStor

Background

Cloud usage is becoming a mandate within organizations looking for ways to manage data growth and improve operational efficiency, while reducing costs. The challenge for organizations is understanding how to consume cloud storage because, by itself, the cloud is often viewed as just infrastructure or a platform-as-a-service. A software layer or software-as-a-service to make cloud storage consumable and relevant to an organization’s needs and ongoing strategy is missing. The market wants an easy way to not only consume cloud storage, but also to put data in or pull it out without being locked in.

Topics: Storage Data Platforms, Analytics, & AI Cloud Services & Orchestration

ESG Technical Review: Analyzing the Performance of MapR-DB, a NoSQL Database in the MapR Converged Data Platform

Abstract

This ESG Technical Review documents and analyzes MapR-DB performance test results. Testing evaluated the performance and scalability of MapR-DB running in the cloud, and we compare results with other leading NoSQL database offerings.

Topics: Data Platforms, Analytics, & AI Cloud Services & Orchestration

ESG Lab Review: Dell EMC Digital Platform for Enterprise Assets and Internet of Things

Abstract

This ESG Lab Review looks at how businesses drive outcomes with the use of Dell Technologies and Dell EMC assets. The Dell EMC assets include a turnkey platform consisting of Native Hybrid Cloud and Analytic Insights Module as part of Dell EMC Converged platforms and solutions. ESG Lab observed how Dell Technologies can empower organizations to:

  • Define their approach to augmenting digital transformation with IoT (Internet of Things) and surveillance technologies with persona-driven use cases.
  • Blend video-based, visual verification with IoT and enterprise data to move beyond traditional surveillance and security investigation and enhance customer experiences, identify overhead, respond to incidents, and collect evidence.
  • Understand how to evaluate and extend an infrastructure for enterprise IoT—core, edge, and cloud—with data transparency and right-time intelligence.
  • Accelerate maturity progression from proof of value to production, including multi-data center, mission-critical deployment.
Topics: Storage Networking Data Platforms, Analytics, & AI

ESG Lab Validation: Replicating Oracle Databases with Quest SharePlex Compared to Alternative, Legacy Products

 

Introduction

ESG Lab evaluated SharePlex from Quest Software with a focus on its ability to replicate Oracle databases easily and quickly, while delivering easy installation and operations, high performance, and ease of use as compared to alternative, legacy solutions.

Topics: Data Protection Data Platforms, Analytics, & AI

ESG Lab Review: Dell EMC Analytic Insights Module: Simplifying Big Data Analytics

Abstract

ESG Lab recently completed testing of Dell EMC’s Analytic Insights Module, which is designed to enable organizations to analyze and extract value from big data more easily. Testing examined how Analytic Insights Module gathers, analyzes, and acts on data—with a focus on ease of use, collaboration, time savings, data security, and simplified data integration.

Topics: Data Platforms, Analytics, & AI

ESG Lab Review: Robin Systems: Container-based Virtualization for Databases and Data-centric applications

Abstract

This ESG Lab Report highlights the recent testing of Robin Container-Based Virtualization Platform. Using a combination of guided demos and audited performance results, ESG Lab validated the ease of use, performance, scalability, and efficiency of Robin Systems’ container-based architecture.

Topics: Data Platforms, Analytics, & AI Cloud Services & Orchestration

ESG Lab Review: MapR Converged Data Platform with MapR Streams

The Challenges

Most organizations have an existing BI/analytics strategy. Many of these strategies consist of a mix of overlapping BI/analytics tools with a focus on batch processing—analyzing piles of data that have already been collected, stored, transformed, merged, cleansed, etc. Now that the Internet of Things is more than a buzz word, the early-adopters are starting to re-evaluate their BI/data analytics approaches. Their existing solutions are already overwhelmed with massive quantities of data and IoT will only add to the complexity. Whether it’s web applications tracking user clicks, sensors collecting weather data, or simply machine log data from within a single IT infrastructure, massive amounts of data are being generated every second and organizations are looking for any way possible to harness that data as soon as it’s collected.  As such, ESG research shows that 45% of organizations are planning to deploy a new BI/analytics solution over the next 24 months. And what is the top requirement for driving the evaluation process? The move to a more real-time analytics approach (Figure 1).[1] This same research also supports the idea that current BI/analytics solutions do not meet existing requirements and needs (26%) because new applications are generating new data types that need different analytical tools (27%).

Topics: Data Platforms, Analytics, & AI