Independent Research Firm Identifies Multimodel Data Platforms (MMDPs) as “The Missing Layer in Your AI Stack” for AI and Agentic Architectures SAN FRANCISCO & Independent Research Firm Identifies Multimodel Data Platforms (MMDPs) as “The Missing Layer in Your AI Stack” for AI and Agentic Architectures SAN FRANCISCO &

Arango Recognized in Analyst Report, The Multimodel Data Platforms Landscape, Q4 2025

Independent Research Firm Identifies Multimodel Data Platforms (MMDPs) as “The Missing Layer in Your AI Stack” for AI and Agentic Architectures

SAN FRANCISCO & COLOGNE, Germany–(BUSINESS WIRE)–#AIInfrastructure–Arango, a provider of Contextual AI data infrastructure, today announced that it has been recognized in Forrester’s report, The Multimodel Data Platforms Landscape, Q4 2025, authored by Indranil Bandyopadhyay, which provides an overview of 18 vendors in the multimodel data platforms (MMDP) market. The report is intended to help technology and data leaders understand the value they can expect from an MMDP vendor, learn how vendors differ, and evaluate options based on size and market focus.

Forrester defines an MMDP as:

A common data platform that provides storage, processing, and access to any data — whether structured, unstructured, or semistructured — and supports multiple data models, such as document, graph, relational, and key-value, for applications and insights.

In their October 2025 report, “Multimodel Data Platform: The Missing Layer In Your AI Stack,” Forrester identifies MMDPs as a means for enabling AI systems to deliver accurate, explainable, context-aware outcomes at scale.

“You can use multimodel data platforms to simplify architectural complexity, enhance developer agility and productivity, and power the ‘brain’ and ‘memory’ of AI agents… MMDPs form the cognitive core of agentic AI by integrating reasoning and memory into a single platform,” states the Landscape report, authored by Indranil Bandyopadhyay, principal analyst at Forrester.

The Forrester report highlights that MMDPs are purpose-built to power the “brain” and “memory” of AI agents, eliminating the critical bottlenecks of traditional architectures where agents must navigate fragmented data silos that increase latency and degrade decision velocity. By natively fusing graph models for reasoning, document and vector models for memory, and key-value models for ground truth, MMDPs enable fast, accurate, and cost-effective responses through a single high-performance query.

The report confirms that most enterprise data architectures were not built for the way modern AI works, as AI systems need to retrieve and reason across graph relationships, vector embeddings, documents, events, and transactional data, often in real time.

Forrester asked each vendor included in the Landscape to select the top use cases for which clients select them and from there determined which are the extended use cases that highlight differentiation among the vendors. The report identifies extended use cases that buyers frequently pursue beyond core MMDP scenarios. Arango is shown in the report for having selected power AI (including agentic AI), operational 360-degree view, and digital twin modeling as top reasons clients work with them out of those extended use cases.

In the report’s vendor landscape, Arango is recognized among vendors offering flexible deployment options, including on-premises, hosted private SaaS, and multitenant SaaS.

“Companies are under pressure to deliver better business outcomes from AI projects that drive trust and adoption, including building AI they can trust, running it at scale, and achieving better economics by reducing data-stack complexity,” said Shekhar Iyer, CEO of Arango. “We believe Arango’s inclusion in Forrester’s Multimodel Data Platforms Landscape reflects the increasing demand for platforms that unify data models to support real-time, multimodal, and agentic AI workloads.”

Resources

  • Get access to the Forrester Multimodel Data Platforms Landscape, Q4 2025 report.
  • Join us for The Missing Link in the AI Stack: Why Data Architecture Determines AI Success or Failure, featuring Indranil Bandyopadhyay, principal analyst at Forrester and the author of this report.
  • Learn more about Arango: arango.ai

About Arango

Arango delivers the Contextual AI Data Infrastructure that forms a unified System of Context, helping enterprises build AI they can trust, run at scale, and achieve better economics. With Arango, teams get the trusted data foundation needed to deliver explainable, accurate outcomes grounded in real business context, so AI decisions are transparent and reliable. As AI initiatives grow, Arango enables organizations to deploy with confidence, scaling across multimodel data without adding complexity. By unifying graph, vector, document, key-value, and search in a single platform, Arango helps shift resources from integration to innovation — freeing teams to focus on building what matters most.

Trusted by NVIDIA, HPE, the London Stock Exchange, the U.S. Air Force, NIH, Siemens, Synopsys, and Articul8, Arango powers enterprise AI with context, confidence, and scale. Arango is a proud member of the NVIDIA Inception Program and the AWS ISV Accelerate Program. Learn more at arango.ai, LinkedIn, and G2.

Forrester Objectivity Statement

Forrester does not endorse any company, product, brand, or service included in its research publications and does not advise any person to select the products or services of any company or brand based on the ratings included in such publications. Information is based on the best available resources. Opinions reflect judgment at the time and are subject to change. For more information, read about Forrester’s objectivity.

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