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The Forrester Wave: Multimodel Data Platforms

Forrester Research

Multimodel Data Platforms Accelerate Deployment Of New Apps And Insights

Forrester Wave™: Multimodel Data Platforms, Q3 2021

Segregating data based on data types and models often slows down data access and leads to data and administration challenges. Multimodel data platforms represent the intersection of multiple data models such as document, graph, and relational in a single data platform, offering speed, scale, performance, integration, and security over the polyglot persistence model. Combining multimodel data types and models on large-scale memory helps deliver real-time, consistent, and trusted data to support new business requirements. Most organizations leverage multimodel data platforms to support microservices-based applications and a common data platform for customer 360, fraud detection, internet-of-things (IoT) analytics, and highly interactive edge applications.

As a result of these trends, multimodel data platforms customers should look for providers that:

  • A platform that delivers built-in speed, scale, and security to meet your requirements. 
  • A platform that can support multimodel apps and insights quickly through automation.
  • A roadmap that is as bold as your multimodel ambitions.

About InterSystems

Forrester has recognized the InterSystems IRIS Data Platform™ as a Leader in The Forrester Wave™: Multimodel Data Platforms, Q3 2021

Forrester defines a multimodel data platform as “the intersection of multiple data models such as document, graph, and relational in a single data platform, offering speed, scale, performance, integration, and security over the polyglot persistence model.”

InterSystems IRIS earned the highest scores possible in the report in:

  • Strategy Execution
  • Technical Support
  • Product Revenue
  • Install Base

According to Forrester InterSystems IRIS is “The platform eliminates the need to integrate multiple technologies, resulting in less code, fewer system resources, and less maintenance. Customers use it to support customer analytics, IoT, AI/ML-enabled apps, risk analytics, and vertical-specific use cases such as healthcare apps and insights.”

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