Metadata Management Solutions Reviews and Ratings
What are Metadata Management Solutions?
Gartner defines metadata management solutions as applications to enable the collection, analysis and orchestration of metadata related to organizational data assets. These solutions enable workflow and operational support to make data easy to find, use and manage. They do this by collating metadata in any form from within its own application and third-party systems, and providing the ability to search, analyze and make decisions on the collated results. They also provide transparent cross-referencing over all related metadata, and derive insights from data (such as usage patterns and performance) through analysis of metadata to support a wide range of data-driven initiatives.
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The Alation Data Intelligence Platform is an enterprise-grade, agentic data intelligence and governance platform that powers people and AI agents with trusted data and knowledge to deliver measurable business outcomes. Alation differentiates through active metadata and agentic capabilities, combining behavioral signals, lineage, governance context, data quality and AI-powered agents to surface risk, automate governance actions, flag data quality issues and support governed data products. By embedding trusted data knowledge directly into analytics tools, workflows, and AI-driven processes, Alation enables organizations to operationalize data and AI with confidence at scale.
Collibra frees your data from the constraints of silos by unifying data and AI governance across your entire ecosystem, regardless of source or compute engine, for ultimate flexibility in how you manage data. Our Collibra Platform gives you automated visibility, control and tracing from input through output, and it automates documentation and data traceability for AI use cases to power speed, data observability and safety. Our enterprise metadata graph enriches data context with every use, and our intuitive UX brings technical and business users into the fold to access and steward data.
Accelerate and strengthen every data and AI use case when everyone in your organization can trust, comply and consume.
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.
Microsoft Azure Data Catalog (Legacy) is a cloud-based metadata management software that enables organizations to register, discover, understand, and consume data sources. The software provides a central repository where users can document data assets, annotate metadata, and search for data using various attributes. It supports collaboration by allowing users to contribute knowledge about data assets, enhancing data discoverability and understanding within organizations. Azure Data Catalog (Legacy) addresses the business problem of data silos and lack of data visibility by facilitating the cataloging and sharing of structured and unstructured data sources across enterprise environments.
Oracle Enterprise Metadata Management is software designed to help organizations manage, govern, and analyze metadata across diverse data sources and environments. The software provides capabilities for capturing, integrating, and maintaining metadata from databases, business intelligence tools, data integration systems, and big data platforms. It enables users to visualize data lineage, trace dependencies, and understand data flows, supporting impact analysis and regulatory compliance efforts. By centralizing metadata management, the software assists businesses in improving data transparency, streamlining governance practices, and enhancing overall data quality within their enterprise information architecture.
erwin Data Intelligence is software designed to provide data governance, cataloging, and data literacy capabilities for organizations managing complex data environments. The software enables users to discover, catalog, and document metadata while supporting data lineage and classification requirements. Through automated harvesting and data mapping, erwin Data Intelligence assists with tracking data movement and usage across systems. The software helps organizations address compliance, data privacy, and risk management by creating a centralized view of data assets and establishing roles and policies for data stewardship. It also offers features for collaboration and knowledge sharing to enhance understanding and usage of enterprise data.
ALEX is a software developed to address data management and governance requirements within organizations. The software offers features such as metadata management, data cataloging, and data lineage, which facilitate the organization and discovery of data assets. By providing automated data classification, policy enforcement, and integrated workflow tools, the software supports compliance with data regulations and enhances transparency across data ecosystems. The software aims to streamline the process for business and technical users to locate, understand, and utilize enterprise data, contributing to improved decision-making and operational efficiency. If no information is found please return No Profile found else return the description.
Atlan is a software designed to streamline data collaboration and governance within organizations by providing a unified workspace for data teams. The software offers features such as automated metadata cataloging, data discovery, and lineage tracking to help users manage and understand their data assets. It supports integrations with various data sources and tools, enabling teams to connect, document, and organize data from diverse environments. Atlan enables policy enforcement, access controls, and compliance workflows to support governance requirements. By centralizing data asset management, the software addresses challenges related to fragmented data ecosystems, improving visibility, accessibility, and trust in organizational data.
Dataedo is a software designed for data cataloging and metadata management that helps organizations document, understand, and govern their data assets. The software enables users to create comprehensive data dictionaries and interactive ER diagrams, facilitating visibility into databases, data warehouses, and business intelligence environments. Dataedo provides features for tracking data lineage, managing data documentation, and sharing insights with stakeholders, supporting compliance, data governance, and collaboration across teams. By offering searchable catalogs and collaborative documentation tools, the software addresses challenges related to data discovery, transparency, and knowledge transfer within enterprises, aiding efficient management and use of data resources.
DataGalaxy provides a collaborative platform to manage active metadata across all data domains. It centralizes business glossaries, technical metadata, data lineage, and object relationships to ensure a shared understanding of data.
The platform supports automated lineage, semantic layers, and AI-powered features such as batch and on-demand description generation and multilingual translation.
Each object can be enriched, linked, and maintained through structured workflows with clear roles and lifecycle status.
With 70+ connectors and a flexible model, DataGalaxy ensures metadata remains actionable and aligned with evolving organizational needs, supporting both day-to-day data usage and long-term data strategy.
IBM watsonx.data intelligence helps organizations curate, manage, and utilize data by leveraging the power of AI to simplify data delivery across hybrid ecosystems. IBM watsonx.data intelligence is a comprehensive solution that integrates capabilities such as data governance (formerly IBM Knowledge Catalog), data lineage (formerly IBM Manta Data Lineage), data sharing, and data quality management. It empowers organizations to discover, trust, and access meaningful data, providing consumers with reliable data products. A Demo Library and a Free Trial are available on the product page showcasing product features and use cases.
IBM InfoSphere Information Server is a software designed to facilitate data integration, data quality, and data governance within organizations. The software enables users to connect, cleanse, and transform large volumes of data from multiple sources, helping ensure the consistency and reliability of enterprise information. It provides capabilities for metadata management, data profiling, and lineage tracking, which support compliance and regulatory requirements. The software offers flexible tools for building, deploying, and managing data management solutions, assisting organizations in organizing and delivering trusted data to support business analytics, decision-making, and operational processes.
SAP Information Steward is a software that provides tools for managing and improving data quality and metadata management within enterprise environments. It enables organizations to analyze, monitor, and report on the quality of their data and track lineage and relationships between different data assets. The software features data profiling, validation, cleansing, and metadata cataloging capabilities, supporting compliance and governance requirements. It addresses business challenges related to inconsistent, incomplete, or inaccurate data by offering comprehensive views into data quality issues and facilitating collaboration between business and IT users to ensure reliable information for operational and analytical use.
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.
The Data Catalog Platform helps organizations eliminate data silos, share knowledge, and deliver on the promise of enterprise AI. The cloud-native platform unlocks data team productivity with automation-powered applications for data discovery, data governance, and DataOps. The Platform provides the trust and verification to keep everyone aligned with the most accurate data for business decision making.
The data.world Data Governance application makes it simple to address the most common and time-consuming tasks facing data governance teams. The result is more productive, strategic data governance that enables productive data and analytics with automations and automation-driven workflows.
data.world’s Data Catalog application accelerates data discovery with AI-assisted search, contextual results, auto-enrichment, and extensive data lineage. Ask natural-language questions of your data, including follow-up inquiries, to ensure users find the right information no matter their expertise.
Solidatus data lineage helps the world’s most complex organizations understand and truly trust the data at the foundation of their business decisions, governance, transformation projects, AI, and more - by helping them discover, assess and prove the complete journey of their data from its source, through multiple systems, to finish. This is done through a visual map of data’s journey and transformations through all systems in an organization. From a complete view through all systems, to drilling deep into a column in a table, for root cause and impact analysis. This helps businesses be proactive, not reactive, in trusting business data. To prove to regulators they're compliant, to the board, customers, and shareholders that decisions and information in annual reports are founded on correct information, that data products are high quality, and that the source of AI initiatives is trusted, transparent data.
Metadata Manager Business Glossary (Legacy) is a software designed to help organizations define, manage, and standardize business terms and their associated metadata within an enterprise environment. The software provides a central repository for business vocabulary, enabling users to access clear definitions and contextual information about data assets. It supports the alignment of business and IT by facilitating consistent use of terminology across data sources, processes, and reports. The software aids in data governance and regulatory compliance efforts by allowing documentation and tracking of data lineage, ownership, and stewardship. Through these features, the software addresses challenges related to inconsistent data understanding and improves overall data quality and collaboration across business units.
Precisely Data360 is a software designed to facilitate data governance, data quality, and metadata management for organizations managing complex data environments. The software provides features for automated data quality assessment, cataloging, data lineage tracking, and policy enforcement to ensure consistent and accurate data throughout business processes. It supports collaboration among data stewards and integrates with enterprise systems to streamline workflows related to compliance, risk mitigation, and business analytics. Precisely Data360 addresses challenges such as inconsistent data standards and lack of transparency by offering tools for documenting, managing, and monitoring data across the data lifecycle.
Rocket Data Intelligence is a software designed to help organizations manage, discover, and analyze their enterprise data assets across various platforms. The software enables users to map, catalog, and classify information, facilitating better understanding of data lineage and relationships. It supports compliance efforts by allowing users to track data usage and monitor sensitive information. Rocket Data Intelligence provides visualization tools for data flow and identifies redundancies for more efficient data management. The software aims to simplify data governance processes and increase transparency, assisting organizations in addressing data quality challenges and supporting decision-making through improved data visibility.
Adaptive Metadata Manager (Legacy) is a software designed to facilitate the management, integration, and governance of metadata within an organization’s information systems. The software provides capabilities for capturing, modeling, and maintaining metadata related to data sources, processes, and business rules. It enables users to visualize relationships between data elements, track data lineage, and establish metadata standards for compliance and auditing purposes. By centralizing metadata, the software helps organizations improve data quality, enhance regulatory compliance, and support decision-making processes by providing a clear view of information assets and their dependencies across heterogeneous IT environments.
Features of Metadata Management Solutions
Updated January 2026Mandatory Features:
Data lineage: Solutions must include the ability to track the first use of data elements within the enterprise throughout all instances of reuse, transmission, transformation, dependencies, and refactoring. This includes duration, frequency, volumes and user-to-use-case associations across its life cycle from source to destination.
Metadata operational support: Solutions must be able to support workflows and document metadata to complete operational management tasks such as data classification, access rights, data privileges/restrictions, process flow monitoring and other operational support tasks. They must be able to continuously capture operational logs and designs as well as runtime metadata from newly added data processes.
Metadata search and sharing: Solutions must enable users to search and explore metadata via a user interface, as well as graph-based visualizations of metadata relationships, usage, tagging and annotations. Additionally, solutions should make their metadata available for direct access or export in as comprehensive and complete a form as possible. Solutions should also aggregate and manage metadata from disparate data catalogs across an organization and provide a “single pane of glass” for discovering and accessing enterprise data assets. Metadata sharing should also be available via data download, API calls, or a data marketplace.
Metadata curation and analysis: Solutions must allow users to enrich metadata contents by creating additional metadata such as tags, comments or labels. Users can also link metadata assets to each other with user inputs that describe the cross-reference purpose for linking any two or more metadata assets. They can also analyze metadata collected from various sources to produce insights into data such as data usage patterns and performance across applications, data stores, use cases and user communities.
Metadata discovery: Solutions must be able to scan various data sources such as databases, applications, spreadsheets, XML files, media and content as well as other unstructured asset types to identify, extract and create metadata. Vendors should provide connectors or bridges for a wide range of data sources and systems including modern data stacks as well as legacy data environments. They should also include the ability to access directly or ingest metadata from beyond their native platform or suite of tools in which they are designed for deployment. Periodic updates regarding changes of use, design, distribution and management of data assets can be scheduled via event-based triggers or models that automatically recognize changes.
Data profiling: Solutions must provide statistical analysis of datasets to understand their structure, content and quality. This process involves collecting statistics and informative summaries about the data, which can help to identify data quality issues, such as missing values, inconsistencies and anomalies.
Ontology and taxonomy management: In a broad sense, metadata provides inputs to derive specific taxonomy from the enterprise data corpus. A solution must have an interface for reviewing the metadata as it develops and then editing the discovered relationships. The interface can take any of several forms. A simple tabular inventory is the minimum, but dictionary, catalog and glossary capabilities are more desirable. The ability to evaluate how the discovered taxonomy can be enriched to build, enhance or challenge ontology concepts within the enterprise is also highly desired.
Rules management: Solutions must enforce business rules that are tied to data elements and associated metadata. This capability provides dedicated interfaces for the definition and creation of rules or policies based on requirements from compliance, business operation, workflow or data quality. Solutions should also include the management of rules life cycles including versioning, certification, exception handling and alerts.

















