Data Management Platforms

Data Management Platforms Reviews and Ratings

What are Data Management Platforms?

Gartner defines data management platforms as integrated, dynamic data environments for managing enterprise data with operational simplicity. DMPs bring different data management capabilities into a single platform, enabling technical and business users to efficiently manage data for operational, analytical and AI use cases. DMPs use shared metadata to automate data management activities, paving the way for more advanced data ecosystems. A DMP is a commercial solution from a single vendor for managing general-purpose data for an organization, unlike a customer data platform.

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Databricks Data Intelligence Platform

By Databricks

(1 Rating)

Databricks is a global company focusing on data and AI. At the core of Databricks is the Databricks Data Intelligence Platform which allows entire organizations to use data and AI to power a wide range of business use cases. It's built on a lakehouse to provide an open, unified foundation for all data and governance and is powered by a Data Intelligence Engine that understands the uniqueness of the organizations’ data. Databricks simplifies and accelerates enterprises' data and AI goals by unifying data, analytics and AI on one platform. Its key mission is to assist data teams in addressing some of the world's most challenging problems.

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Denodo Platform

By Denodo

Denodo is a data management company offering solutions that facilitate access to a variety of data sources, such as enterprise, big data, and cloud. The core business problem it addresses is the streamlining of data services provisioning and governance with a lower cost approach. Denodo has developed a unified virtual data layer that fulfils strategic, enterprise-wide information requirements for big data analytics, web and cloud integration, SOA data services, and single-view applications. Its platform also provides access to structured and unstructured data located in multiple locations. It serves data-focused organizations with analytical and operational needs. Denodo's platform aspires to deliver agility, faster route to market capabilities, enhanced customer interaction through a complete customer view, and operational efficiency through real-time business intelligence. Incepted in 1999, the company is headquartered in Palo Alto and operates from 25 offices across 20 countries.

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Informatica Intelligent Data Management Cloud

By Informatica

Informatica is a firm specializing in Enterprise Cloud Data Management which aims to allow businesses to fully utilize their most significant assets. Inventing a fresh category of software, the Informatica Intelligent Data Management Cloud (IDMC), the firm utilizes AI to manage data across multi-cloud, hybrid systems. This innovation offers modern, advanced business strategies by democratizing data. With a global reach, the company is focused on driving digital transformation powered by data. The firm's tagline is, 'Where data comes to life'.

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Microsoft Fabric

By Microsoft

Microsoft enables digital transformation for the era of an intelligent cloud and an intelligent edge. Its mission is to empower every person and every organization on the planet to achieve more. Microsoft is dedicated to advancing human and organizational achievement.

Microsoft Security helps protect people and data against cyberthreats to give peace of mind.

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SAS Viya

By SAS

SAS is a global leader in AI and analytics software, including industry-specific solutions. SAS helps organizations transform data into trusted decisions faster by providing knowledge in the moments that matter. SAS gives you THE POWER TO KNOW®.

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Features of Data Management Platforms

Updated November 2025

Mandatory Features:

Data integration: Capabilities for extraction, ingestion, transformation and delivery of data using a combination of common data integration styles, such as batch data movement, data replication and synchronization, stream data integration and data virtualization.
Data governance policy execution: Capabilities that integrate governance controls directly into data pipelines, thereby guaranteeing governance and compliance consistency. The platform should support the governance of data across business domains, when necessary.
Unified platform: Data management capabilities — like data integration, metadata management and governance policy execution — are preintegrated as a platform using a common infrastructure that offers seamless and consistent interaction across the various capabilities.
Platform-based pricing: the platform offers serverless cloud computing via a consumption-based pricing model with common units (or platform credits). Additionally, the platform provides features to evaluate an organization’s consumption by different projects and workloads.
Data quality: Capabilities for data profiling, cleansing, validating business rules, identifying and resolving errors and outliers in data.
Metadata management: Capabilities that access and integrate different forms of metadata (technical, business, operations and social), standardize the collated results, and enable relevant search and analysis. The platform should enable metadata analysis that increases data utilization and reduces governance complexity.
Support for data persistence: Capabilities to manage data storage in a durable manner with full multimodel support, enabling a full range of create, read, update and delete (CRUD) operations, and atomic, consistent, isolated and durable (ACID) compliance. Here, “support” indicates that the platform doesn’t have to persist data like a database, but support databaselike operations on persistent data; for example, pushdown and managing cloud object stores is acceptable.