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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.
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.
Progress Data Platform software enables organizations to connect, integrate, and manage diverse data sources across on-premises and cloud environments. The software offers data connectivity, integration tools, and management capabilities to support business intelligence, analytics, and operational applications. It supports a range of database systems, applications, and cloud services, providing unified access to structured and unstructured data. Progress Data Platform software addresses business challenges related to siloed information and data complexity by simplifying data access and integration, enabling organizations to streamline data workflows and extract actionable insights from multiple sources in real time.
Microsoft Fabric is a data analytics software that integrates multiple tools for data integration, data engineering, data warehousing, data science, real-time analytics and business intelligence into a single platform. The software supports connectivity across sources and provides a unified experience for data preparation, transformation and modeling. Microsoft Fabric enables organizations to store, manage and analyze data from various sources by offering access to lakehouse architecture, semantic models and reporting features. The software addresses challenges related to disparate data tools and data silos by offering centralized governance, security and collaboration functions aimed at streamlining analytics processes for business decision-making.
SAS Viya is a software platform designed for data management, analytics, and artificial intelligence tasks. It supports a range of analytical methods including data preparation, statistical analysis, machine learning, and deep learning. The software enables users to integrate data from multiple sources, perform complex data transformations, and build analytical models. SAS Viya supports collaborative workflows, allowing different users to access and work on data projects using a common platform. It offers programming interfaces in languages such as Python and R and provides deployment options that accommodate on-premise, cloud, and hybrid environments. The software addresses the challenge of deriving insights from large and diverse datasets to enable data-driven decision making in organizations.
Databricks Data Intelligence Platform is a software designed to unify data, analytics, and artificial intelligence workloads under a single platform. It enables organizations to store, manage, and analyze structured and unstructured data at scale while supporting collaborative data engineering, machine learning, and business intelligence projects. The software provides tools for data warehousing, data lakehouse integration, automated data workflows, and governance capabilities, facilitating secure sharing and discovery of data assets. By streamlining the creation of analytics solutions, Databricks Data Intelligence Platform aids businesses in deriving insights, building machine learning models, and operationalizing data science processes to address complex analytical tasks and inform decision-making.
Informatica Intelligent Data Management Cloud is a software designed to facilitate data integration, management, and analytics across various cloud and on-premises environments. The software provides capabilities for automating data pipelines, cleansing, cataloging, and transforming data to support improved data quality and governance. It enables organizations to connect and unify disparate data sources, manage data workloads, and ensure data availability for analytics and reporting. The software addresses business challenges related to data fragmentation, complexity in multi-cloud environments, and regulatory compliance by providing centralized control and monitoring functionalities, helping businesses leverage their data for operational and strategic decision-making.
Amazon SageMaker is the center for all your data, analytics, and AI. Its open data foundation is built on Amazon S3 and Apache Iceberg, supporting multiple query engines such as Amazon Redshift, Amazon Athena, and third-party options through federation. Consistent governance and metadata span every workload with SageMaker Catalog, fine-grained access controls, and full lineage so teams can discover, trust, and secure their data in one place. From this foundation, teams work in a single development environment to build ETL pipelines, query data in SQL, and create analyses in serverless notebooks, all accelerated by the built-in data agent. They can also train and deploy ML and foundation models with SageMaker AI (including HyperPod, JumpStart, and MLOps), and build agentic workflows with Amazon Bedrock and AgentCore in the same platform. SageMaker meets developers where they are with remote IDE connectivity and open protocol support so people and agents can use it programmatically.
Alibaba Cloud DataWorks is a data integration and management software designed to support big data development and governance across various data environments. The software provides capabilities such as data ingestion, development, scheduling, and monitoring, enabling users to build and operate data pipelines. It offers features including data modeling, workflow orchestration, data quality assurance, metadata management, and centralized collaboration. DataWorks allows for integration with multiple data sources and supports development in several programming languages. The software addresses business needs for secure, compliant, and scalable processing of structured and unstructured data, supporting analytics and decision-making by organizing data assets across an organization.
Denodo Platform is a data virtualization software that enables organizations to access, manage, and integrate data from multiple heterogeneous sources without moving the data from its original location. The software provides a unified data layer for real-time data access, supporting analytical and operational use cases. It features capabilities for metadata management, data governance, data security, and performance optimization. Denodo Platform addresses the challenge of data silos by facilitating a single point of access to distributed data sources, helping organizations gain insights and make informed business decisions without replicating or physically consolidating data.
Ab Initio is a data processing software designed to support complex data integration, transformation, and analysis tasks. The software provides a graphical environment for designing data workflows and enables users to process large volumes of structured and unstructured data. Ab Initio offers features for data extraction, cleansing, validation, and loading across multiple heterogeneous sources. The software supports parallel processing and scalability to address enterprise data integration needs, and it enables automation of repetitive tasks and monitoring of data pipelines. Ab Initio is used to solve business problems related to data movement, quality, and analytics, supporting both batch and real-time processing requirements.
ChainSys Smart Data Platform is a low/no-code, template-driven enterprise data management platform that simplifies data across ERP, SaaS, cloud & on-premises systems. Powered by 10,000+ prebuilt templates, it enables faster migration & integration while ensuring up to 99.9% data quality.
The platform unifies data movement, governance, metadata, analytics & security under a centralized control layer to standardize & manage enterprise data.
dataZap – Data Integration, Migration & Archival
Enables reliable data movement across systems, supporting integrations, migrations, archival & large-scale data processing with rule-based execution.
dataZen – Data Quality, Governance & Master Data Management
Ensures trusted enterprise data through validation, cleansing, governance workflows, approvals & master data control.
dataZense – Metadata Management, Analytics & Data Security
Provides active metadata, lineage, analytics, and policy-driven security to improve data
DataOS is a Data Product Platform that empowers data teams to efficiently and collaboratively build, deploy, and manage Data Products at scale. It brings a new data architecture paradigm that democratizes data product development and enables a reusable, modular, and composable operating platform that fosters innovation, increases developer efficiency, lowers data OpEx, and improves business autonomy and agility. DataOS leverages existing data infrastructure, abstracts multi-cloud complexity, automates DataOps, and optimizes the overall developer experience.
Infoveave is an AI powered data automation and decision intelligence platform. The software offers features for data integration, process automation, reporting, and analytics. Infoveave supports the collection, transformation, and analysis of structured and unstructured data, enabling users to automate repetitive tasks and generate customizable reports. It allows businesses to monitor key performance indicators and trends through dashboards and visualizations. The software aims to address business challenges related to manual data handling and process inefficiencies by streamlining data workflows and enabling data-driven decision making.
With Fovea, Agentic AI assistants, Infoveave simplifies data engineering, accelerates insight discovery, and enables business users to interact with data using natural language. The platform supports self-service analytics while maintaining enterprise-grade governance and control.
K2view Data Product Platform is an AI-powered data management platform that delivers governed, complete, and real-time operational context for operational, analytical, and AI use cases. It composes data from multiple sources into reusable data products organized by business entities such as customers, orders, and products, ensuring full context and consistency. Each data product is continuously updated, secure, and optimized for low-latency access at scale.
The platform unifies metadata management, data integration, virtualization, governance, and synthetic data into a single architecture, with AI-driven automation for discovery, pipeline generation, and data services. With centralized policy enforcement and real-time data delivery, K2view enables enterprises to simplify DataOps, ensure compliance, and accelerate AI-ready data consumption across cloud and on-premises environments.
LakeStack is a software developed by Applify that provides a data platform designed to simplify and manage modern data workloads. The software enables organizations to store, process, and analyze large volumes of structured and unstructured data from multiple sources. It facilitates data pipeline orchestration, centralized data management, and integration with various data storage solutions and analytics tools. LakeStack assists businesses in consolidating disparate data sources, automating data transformation, and supporting data-driven decision making. The software addresses challenges related to data silos, scalability, and real-time processing, enabling users to handle complex data environments while maintaining data integrity and accessibility.
MatrixOne Intelligence is a software designed for data management and analytics, offering features for real-time data processing and analysis. It supports SQL-based querying and enables integration with multiple data sources. The software facilitates transactional and analytical workloads within a single unified platform, helping organizations manage data storage, retrieval, and complex analytical tasks. It aims to assist businesses in deriving insights from structured and unstructured data while ensuring data consistency and concurrency. The software addresses challenges related to big data handling and seeks to streamline information workflows, supporting decision-making processes through efficient data operations.
SAP Business Data Cloud is a software designed to enable organizations to unify, manage, and analyze data from various sources across on-premise and cloud environments. The software provides capabilities for data integration, governance, and sharing, aiming to break down data silos and enhance data-driven decision-making. It supports data modeling, cataloging, and secure collaboration, while offering built-in tools to ensure compliance and data quality standards are met. By streamlining access to trusted business data, the software helps address challenges related to fragmented data landscapes and supports better analytics and business outcomes.
Starburst is the Enterprise Intelligence Platform that connects, organizes, and activates AI on distributed enterprise data — without moving it. Built on enterprise-hardened Trino, Starburst delivers high-performance federated SQL across cloud lakes, warehouses, and operational systems on Apache Iceberg's open table format.
The Enterprise Context Layer organizes distributed data into shared ground truth — serving governed business context, data products, and semantic definitions at query time so humans and AI work from the same trusted foundation.
AIDA, Starburst's AI Data Assistant, connects models, tools, and agents through a governed, model-agnostic agentic layer grounded in certified enterprise data.
Deployed as Starburst Enterprise Platform (SEP) for on-premises/hybrid environments or Galaxy, a fully managed SaaS offering.
Primary use cases: federated analytics, enterprise data products, AI-readiness for regulated industries, and governed agentic workflows.
This service may contain translations provided by Google. Google disclaims all warranties related to the translations, express or implied, including any warranties of accuracy, reliability, and any implied warranties of merchantability, fitness for a particular purpose and noninfringement. Gartner's use of this provider is for operational purposes and does not constitute an endorsement of its products or services.
