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Top 10 Best Data Cataloging Software of 2026

Discover the top 10 best data cataloging software to organize and manage your data effectively. Explore now to find your perfect tool.

Sarah Mitchell

Sarah Mitchell

Feb 11, 2026

10 tools comparedExpert reviewed
Independent evaluation · Unbiased commentary · Updated regularly
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In today’s data-driven business landscape, data cataloging software is critical for organizing, simplifying, and governing data assets—ensuring teams can trust, discover, and leverage information effectively. With a range of options from enterprise-grade platforms to open-source tools, choosing the right solution is key to maximizing data value.

Quick Overview

  1. 1#1: Collibra - Collibra is an enterprise data intelligence platform that enables data cataloging, governance, and stewardship across hybrid environments.
  2. 2#2: Alation - Alation Data Catalog empowers teams to discover, understand, and trust data through AI-driven search and collaboration features.
  3. 3#3: Informatica Enterprise Data Catalog - Informatica Enterprise Data Catalog automates metadata scanning and provides a unified inventory of enterprise data assets with lineage.
  4. 4#4: Microsoft Purview - Microsoft Purview unifies data cataloging, governance, and compliance across multi-cloud and on-premises data estates.
  5. 5#5: Atlan - Atlan is an active metadata platform that combines data cataloging with real-time collaboration and automation for modern data teams.
  6. 6#6: Google Cloud Data Catalog - Google Cloud Data Catalog offers a fully managed metadata service for discovering and enriching data across Google Cloud.
  7. 7#7: DataHub - DataHub is an open-source metadata platform for data discovery, lineage, and observability in large-scale environments.
  8. 8#8: Amundsen - Amundsen is an open-source data discovery and metadata engine designed for indexing and searching data assets.
  9. 9#9: Talend Data Catalog - Talend Data Catalog provides automated data discovery, semantic mapping, and quality assessment for enterprise data.
  10. 10#10: OvalEdge - OvalEdge is an AI-powered data catalog and governance tool for automating metadata management and data lineage.

We evaluated tools based on core capabilities (metadata management, lineage, discovery), user experience, scalability, and long-term value, prioritizing those that deliver robust performance across hybrid, multi-cloud, and on-premises environments.

Comparison Table

This comparison table features leading data cataloging tools such as Collibra, Alation, Informatica Enterprise Data Catalog, Microsoft Purview, Atlan, and more, designed to guide readers in assessing options. It explores key functionalities, integration strengths, and use cases, helping users identify the tool that best fits their organization's data management needs, from improving data discoverability to enhancing compliance.

1Collibra logo9.4/10

Collibra is an enterprise data intelligence platform that enables data cataloging, governance, and stewardship across hybrid environments.

Features
9.7/10
Ease
8.1/10
Value
8.6/10
2Alation logo9.2/10

Alation Data Catalog empowers teams to discover, understand, and trust data through AI-driven search and collaboration features.

Features
9.5/10
Ease
8.0/10
Value
8.5/10

Informatica Enterprise Data Catalog automates metadata scanning and provides a unified inventory of enterprise data assets with lineage.

Features
9.3/10
Ease
7.4/10
Value
8.1/10

Microsoft Purview unifies data cataloging, governance, and compliance across multi-cloud and on-premises data estates.

Features
9.2/10
Ease
7.7/10
Value
8.1/10
5Atlan logo8.8/10

Atlan is an active metadata platform that combines data cataloging with real-time collaboration and automation for modern data teams.

Features
9.3/10
Ease
8.6/10
Value
8.2/10

Google Cloud Data Catalog offers a fully managed metadata service for discovering and enriching data across Google Cloud.

Features
9.2/10
Ease
7.8/10
Value
8.1/10
7DataHub logo8.7/10

DataHub is an open-source metadata platform for data discovery, lineage, and observability in large-scale environments.

Features
9.3/10
Ease
7.4/10
Value
9.6/10
8Amundsen logo8.1/10

Amundsen is an open-source data discovery and metadata engine designed for indexing and searching data assets.

Features
8.5/10
Ease
6.8/10
Value
9.4/10

Talend Data Catalog provides automated data discovery, semantic mapping, and quality assessment for enterprise data.

Features
8.7/10
Ease
7.4/10
Value
7.9/10
10OvalEdge logo8.0/10

OvalEdge is an AI-powered data catalog and governance tool for automating metadata management and data lineage.

Features
8.5/10
Ease
7.8/10
Value
7.5/10
1
Collibra logo

Collibra

enterprise

Collibra is an enterprise data intelligence platform that enables data cataloging, governance, and stewardship across hybrid environments.

Overall Rating9.4/10
Features
9.7/10
Ease of Use
8.1/10
Value
8.6/10
Standout Feature

AI-powered Data Intelligence Platform with unified catalog, lineage, and governance in a collaborative steward community

Collibra is a premier data intelligence platform specializing in data cataloging, governance, and stewardship, enabling organizations to discover, understand, trust, and govern their data assets at scale. It offers automated metadata management, data lineage, business glossaries, and policy enforcement to ensure compliance and data quality across hybrid environments. With AI-driven insights and collaborative workflows, Collibra empowers data teams to democratize data access while maintaining enterprise-grade controls.

Pros

  • Comprehensive data lineage and impact analysis for full visibility
  • Robust governance workflows and policy management
  • Extensive integrations with BI, ETL, and cloud data platforms

Cons

  • High cost with custom enterprise pricing
  • Steep learning curve and complex initial setup
  • Overkill for small teams or simple cataloging needs

Best For

Large enterprises requiring advanced data governance, compliance, and cataloging across complex, multi-cloud environments.

Pricing

Custom subscription pricing based on data volume and users; typically starts at $50,000+ annually for mid-sized deployments.

Visit Collibracollibra.com
2
Alation logo

Alation

enterprise

Alation Data Catalog empowers teams to discover, understand, and trust data through AI-driven search and collaboration features.

Overall Rating9.2/10
Features
9.5/10
Ease of Use
8.0/10
Value
8.5/10
Standout Feature

AI-powered SQL Copilot that provides real-time query suggestions and explanations

Alation is an enterprise-grade data catalog platform designed to help organizations discover, understand, govern, and trust their data assets across diverse sources. It leverages AI and machine learning for semantic search, automated metadata curation, and data lineage visualization, enabling seamless collaboration among data teams. Key capabilities include SQL copilot for query assistance, trust flags for data quality assessment, and integration with BI tools like Tableau and Power BI.

Pros

  • AI-driven semantic search and auto-tagging for rapid data discovery
  • Robust data lineage and impact analysis for governance
  • Strong collaboration tools including trust flags and community curation

Cons

  • High cost suitable mainly for large enterprises
  • Steep learning curve and complex initial setup
  • Limited customization for smaller teams without professional services

Best For

Large enterprises with complex, multi-source data environments needing advanced governance and collaboration.

Pricing

Custom enterprise subscription starting at around $100,000 annually, based on users, data volume, and features.

Visit Alationalation.com
3
Informatica Enterprise Data Catalog logo

Informatica Enterprise Data Catalog

enterprise

Informatica Enterprise Data Catalog automates metadata scanning and provides a unified inventory of enterprise data assets with lineage.

Overall Rating8.7/10
Features
9.3/10
Ease of Use
7.4/10
Value
8.1/10
Standout Feature

CLAIRE AI engine enabling cognitive search, auto-classification, and natural language queries across the data catalog

Informatica Enterprise Data Catalog (EDC) is an AI-powered metadata management platform that automatically discovers, catalogs, and enriches data assets across on-premises, cloud, and hybrid environments. It leverages machine learning via the CLAIRE engine to scan diverse data sources, profile quality, classify sensitive data, and map technical and business lineage. EDC integrates deeply with Informatica's Intelligent Data Management Cloud (IDMC) suite for comprehensive data governance and impact analysis.

Pros

  • AI-driven automation with CLAIRE for metadata extraction and tagging
  • Extensive library of 200+ connectors for broad data source coverage
  • Advanced lineage mapping and relationship inference at enterprise scale

Cons

  • Complex deployment and configuration requiring specialized skills
  • High licensing costs unsuitable for SMBs
  • Steeper learning curve for non-Informatica ecosystem users

Best For

Large enterprises with hybrid/multi-cloud data estates seeking automated, scalable data cataloging and governance.

Pricing

Subscription-based enterprise pricing, typically $100K+ annually depending on data volume, users, and connectors; custom quotes required.

4
Microsoft Purview logo

Microsoft Purview

enterprise

Microsoft Purview unifies data cataloging, governance, and compliance across multi-cloud and on-premises data estates.

Overall Rating8.6/10
Features
9.2/10
Ease of Use
7.7/10
Value
8.1/10
Standout Feature

Unified Data Map providing a 360-degree view of data assets with automatic scanning and lineage across diverse sources

Microsoft Purview is a unified data governance solution that serves as a powerful data cataloging tool, automatically scanning, classifying, and mapping data assets across on-premises, multi-cloud, and SaaS environments. It offers a centralized data map, business glossary, and end-to-end lineage tracking to enable data discovery, understanding, and compliance. With built-in AI-driven classification and sensitivity labeling, it helps organizations govern their entire data estate efficiently.

Pros

  • Broad support for 100+ data sources including hybrid and multi-cloud setups
  • Advanced lineage visualization and automated data classification
  • Seamless integration with Microsoft ecosystem (Azure, Power BI, Synapse)

Cons

  • Steep learning curve for complex configurations and full governance features
  • Pricing can escalate quickly for large-scale scanning outside Microsoft licensing
  • Less intuitive for non-Microsoft environments compared to specialized catalogs

Best For

Enterprises deeply integrated with Microsoft services seeking comprehensive hybrid data governance and cataloging.

Pricing

Capacity-unit metered pricing (e.g., ~$0.0043/GB/month for Data Map scanning); premium governance included in Microsoft 365 E5 (~$57/user/month) or available as add-ons.

Visit Microsoft Purviewpurview.microsoft.com
5
Atlan logo

Atlan

enterprise

Atlan is an active metadata platform that combines data cataloging with real-time collaboration and automation for modern data teams.

Overall Rating8.8/10
Features
9.3/10
Ease of Use
8.6/10
Value
8.2/10
Standout Feature

Active Metadata, which automates metadata evolution, governance workflows, and contextual enrichment across the entire data stack

Atlan is a modern active metadata platform and data catalog that unifies metadata from diverse sources like data warehouses, BI tools, and ML platforms for seamless discovery and governance. It offers AI-powered search, automated data lineage, contextual enrichment, and real-time collaboration features to help data teams trust and utilize data effectively. Atlan stands out in data mesh architectures by enabling cross-team workflows and integrations with tools like Slack, Teams, and dbt.

Pros

  • AI-driven search and automated lineage for quick data discovery
  • Seamless collaboration via Slack/Teams integrations
  • Robust governance with policy enforcement and compliance tools

Cons

  • Enterprise pricing can be steep for SMBs
  • Initial setup requires metadata connector configuration
  • Advanced customization may need developer support

Best For

Mid-to-large enterprises with distributed data teams needing collaborative governance in data mesh environments.

Pricing

Custom quote-based pricing; typically starts at $20,000+ annually for mid-sized deployments, scaling with usage and seats.

Visit Atlanatlan.com
6
Google Cloud Data Catalog logo

Google Cloud Data Catalog

enterprise

Google Cloud Data Catalog offers a fully managed metadata service for discovering and enriching data across Google Cloud.

Overall Rating8.6/10
Features
9.2/10
Ease of Use
7.8/10
Value
8.1/10
Standout Feature

Automated data lineage visualization across GCP pipelines and services

Google Cloud Data Catalog is a fully managed, metadata management service that helps organizations discover, understand, and manage data assets across Google Cloud Platform (GCP). It provides unified search across diverse data sources like BigQuery, Cloud Storage, and Pub/Sub, while supporting tagging, business glossaries, and data lineage visualization. Designed for data governance, it enables collaboration among data analysts, scientists, and engineers by enriching metadata automatically from GCP services.

Pros

  • Deep integration with GCP services for automatic metadata ingestion and lineage
  • Powerful semantic search with natural language processing and tag-based querying
  • Robust data governance tools including business glossaries and IAM-based access controls

Cons

  • Limited native connectors for non-GCP or on-premises data sources
  • Pricing scales with metadata volume and scans, potentially costly at enterprise scale
  • Requires GCP familiarity, with a steeper setup curve for multi-cloud users

Best For

GCP-centric organizations seeking comprehensive metadata management and discovery for cloud-native data workloads.

Pricing

Free for up to 10,000 metadata entries per region; $1 per 1,000 additional entries/month, plus $0.10 per 1,000 search requests and scan job costs.

Visit Google Cloud Data Catalogcloud.google.com/datacatalog
7
DataHub logo

DataHub

other

DataHub is an open-source metadata platform for data discovery, lineage, and observability in large-scale environments.

Overall Rating8.7/10
Features
9.3/10
Ease of Use
7.4/10
Value
9.6/10
Standout Feature

End-to-end data lineage that traces data flow across pipelines, tables, and ML models in real-time

DataHub is an open-source metadata platform that serves as a centralized data catalog for discovering, understanding, and governing data assets across an organization. It supports metadata ingestion from over 40 connectors, enabling features like full-text search, data lineage visualization, and domain-based governance. Built for scale, it handles massive datasets and integrates with tools like Kafka, dbt, and Snowflake, making it ideal for modern data stacks.

Pros

  • Comprehensive metadata ingestion from 40+ sources with real-time updates
  • Powerful lineage tracking and interactive visualizations
  • Extensible open-source architecture with strong community support

Cons

  • Complex initial deployment requiring Kubernetes expertise
  • Steep learning curve for advanced customization
  • UI can feel overwhelming for non-technical users

Best For

Large enterprises with engineering teams needing scalable, metadata-driven data discovery and governance.

Pricing

Fully open-source and free to self-host; enterprise support available via partners like Acryl Data starting at custom pricing.

Visit DataHubdatahubproject.io
8
Amundsen logo

Amundsen

other

Amundsen is an open-source data discovery and metadata engine designed for indexing and searching data assets.

Overall Rating8.1/10
Features
8.5/10
Ease of Use
6.8/10
Value
9.4/10
Standout Feature

Popularity tracking with badges that dynamically rank datasets based on real usage metrics

Amundsen is an open-source metadata engine and data discovery platform developed by Lyft, designed to help users search, discover, and understand data assets across large-scale environments. It provides semantic search capabilities, dataset lineage visualization, and popularity tracking to promote data trustworthiness and reuse. Integrated with tools like Apache AI rflow and various data warehouses, it enables metadata management without vendor lock-in.

Pros

  • Powerful semantic search with Elasticsearch for quick data discovery
  • Dataset popularity badges and usage stats to identify trusted assets
  • Highly extensible with integrations to major data tools and open-source community support

Cons

  • Complex deployment requiring Kubernetes and significant DevOps effort
  • Limited native support for advanced governance or data quality monitoring
  • Outdated UI and documentation that can hinder onboarding

Best For

Engineering-heavy organizations seeking a customizable, cost-free data catalog for large-scale discovery and metadata management.

Pricing

Fully open-source and free; self-hosting incurs infrastructure costs (e.g., Kubernetes clusters).

Visit Amundsenamundsen.io
9
Talend Data Catalog logo

Talend Data Catalog

enterprise

Talend Data Catalog provides automated data discovery, semantic mapping, and quality assessment for enterprise data.

Overall Rating8.1/10
Features
8.7/10
Ease of Use
7.4/10
Value
7.9/10
Standout Feature

AI-powered Semantic Discovery that automatically detects and maps business relationships across disparate datasets

Talend Data Catalog is a robust data intelligence platform that automates the discovery, cataloging, and governance of data assets from diverse sources including databases, cloud services, and big data environments. It excels in providing end-to-end data lineage, semantic mapping, and quality profiling to enable data teams to understand relationships and trust their data. Integrated seamlessly with Talend's ETL and integration tools, it supports enterprise-scale data management with AI-driven insights.

Pros

  • Automated machine learning-based discovery and semantic relationships
  • Comprehensive data lineage and impact analysis visualization
  • Broad connector support for hybrid and multi-cloud environments

Cons

  • Steep learning curve for initial setup and advanced features
  • Pricing can be prohibitive for small organizations
  • UI feels dated compared to newer competitors

Best For

Mid-to-large enterprises using Talend's data integration suite or needing advanced automated discovery in complex, hybrid data landscapes.

Pricing

Quote-based subscription model, typically starting at $10,000-$50,000 annually depending on data volume, users, and deployment scale.

10
OvalEdge logo

OvalEdge

enterprise

OvalEdge is an AI-powered data catalog and governance tool for automating metadata management and data lineage.

Overall Rating8.0/10
Features
8.5/10
Ease of Use
7.8/10
Value
7.5/10
Standout Feature

AI-powered semantic search that understands natural language queries for intuitive data discovery

OvalEdge is an AI-powered data catalog platform that automates the discovery, cataloging, and governance of enterprise data assets from diverse sources including databases, cloud storage, and BI tools. It offers comprehensive metadata management, interactive data lineage visualization, and collaborative features to enable data democratization and compliance. With semantic search and policy enforcement, it helps organizations build a unified data intelligence layer.

Pros

  • Extensive automated scanning and connector support for 100+ data sources
  • Strong AI-driven semantic search and data lineage capabilities
  • Robust governance tools including stewardship and policy management

Cons

  • Pricing can be steep for smaller organizations
  • Advanced features have a moderate learning curve
  • Performance may lag with very large-scale deployments

Best For

Mid-to-large enterprises seeking an automated, AI-enhanced data catalog for governance and discovery across hybrid environments.

Pricing

Custom enterprise pricing starting around $20,000 annually, based on data volume and users; free trial available.

Visit OvalEdgeovaledge.com

Conclusion

The reviewed data cataloging tools differ in focus—from enterprise hybrid capabilities to AI-driven collaboration and open-source flexibility—yet all empower teams to manage data effectively. Leading the pack, Collibra excels as a comprehensive solution, while Alation stands out for its user-friendly AI discovery and Informatica Enterprise Data Catalog impresses with automation and lineage tools, offering strong alternatives for varied needs.

Collibra logo
Our Top Pick
Collibra

Explore Collibra to unlock seamless data governance and stewardship across your environment, or dive into Alation or Informatica to find the perfect fit for your team’s unique requirements.