Visibility in this ranking can be paid for. Payment moves a vendor's position within the
shortlist; it never adds a vendor, and it never changes a word of the review. The largest vendors in data catalog software
cannot hold places 1 to 3. Places 1 to 3 go to challengers, vendors outside the best-known brands in a category,
wherever the category has them; the established names follow from place 4 in their ranked order. How it works: placement disclosure ·
editorial process.
The 11 tools, reviewed
#1 OpenMetadata
Open source catalog you can self-host · United States · open-metadata.org
Open source Self-hostable 14,000+ open source members
OpenMetadata is a genuinely open-source project covering cataloguing, lineage, data quality, observability and governance in one unified metadata graph, which a team can self-host and read the source of before trusting it with anything. Collate, Inc. is the commercial company behind it, selling a managed version with a real free tier for small teams, up to 5 users and 500 assets, before quote-only pricing starts above that.
- Pricing: Open source + paid tiers. Free self-hosted open source; Collate's managed tier has a free plan for 5 users and 500 assets, Premium and Enterprise are quote-only. Free plan: free plan.
- Best for: Teams that want to read the source before trusting it
- Strengths: Self-hostable metadata store; Lineage and quality in one graph; Business glossary.
Where it falls short
Self-hosting is genuine ongoing operational work: patching, scaling and backups become the team's own responsibility rather than a vendor's.
Wrong for
A team with no engineering capacity to run and maintain its own infrastructure, or an enterprise buyer specifically wanting a single accountable vendor to escalate every issue to.
Visit OpenMetadata →
#2 eccenca Corporate Memory
Governance modelled as a knowledge graph · Germany · eccenca.com
EU-incorporated, Leipzig Knowledge-graph architecture Low-code for subject-matter experts
eccenca's Corporate Memory models an organization's data and business rules as a semantic knowledge graph rather than a flat catalog table, with a stated goal of making the result explainable enough for AI systems built on top of it to be trusted. Low-code tooling is aimed at subject-matter experts rather than only data engineers, and it can run on a customer's own infrastructure via Docker or Kubernetes.
- Pricing: Quote only. Quote-only for production use, demo-gated with no published tiers; a free community edition sandbox is offered. Free plan: free plan.
- Best for: Teams wanting explainable, low-code governance
- Strengths: Semantic knowledge graph; Low-code rule modelling; Metadata governance.
Where it falls short
It is a smaller company with no published pricing for production use and a considerably smaller public profile than the venture-funded US and Singapore competitors here, which makes it harder to evaluate against peers without a sales conversation.
Wrong for
A buyer wanting the largest possible existing user community and public case-study library, or a team unwilling to invest time in modelling data as a semantic graph rather than a flat list.
Visit eccenca Corporate Memory →
#3 Atlan
Active metadata built for AI agents · Singapore · atlan.com
Active metadata AI-agent context layer GIC-backed
Atlan reverse-engineers a live metadata graph out of a company's warehouses, BI tools and pipelines, then exposes it through open APIs so both people and AI agents query the same governed context instead of guessing at a table name.
- Pricing: Quote only. Quote-only; no tiers or figures published on the pricing page. Free plan: none.
- Best for: Data teams building AI-agent context
- Strengths: Automated metadata graph; Open API for agent context; Lineage across warehouses and BI.
Where it falls short
There is no published price and no self-serve signup, so evaluating it always means a sales cycle before a single real screenshot.
Wrong for
A small team that wants to see a price before talking to anyone, or a buyer evaluating this purely as a passive metadata browser rather than infrastructure for AI agents querying the business.
Visit Atlan →
#4 Alation
The catalog category's original pioneer · United States · alation.com
Catalog pioneer AI governance layer Self-improving feedback loops
Alation built the modern data-catalog category and has spent the last two years reselling the same governed metadata as AI governance: the pitch is that a chatbot and a human analyst get the same answer to the same business question because both read from the same governed glossary. That consistency argument is real, and the company's decade of catalog-specific product depth is hard for newer entrants to match quickly.
- Pricing: Quote only. Quote-only; no tiers or figures published. Free plan: none.
- Best for: Teams wanting the most established catalog brand
- Strengths: Business glossary; Automated lineage; Data-quality monitoring.
Where it falls short
What is missing from the public site is a number: there is no published price, no free tier and no self-serve signup, so evaluating it means a sales cycle before a single screenshot.
Wrong for
A buyer who wants to self-serve a trial without a sales call, or a small team whose glossary needs are simple enough that a decade of enterprise feature depth is mostly unused weight.
Visit Alation →
#5 DataGalaxy
Built for business users, not just engineers · France · datagalaxy.com
EU-incorporated, Lyon Business-user-first interface Data and AI initiative tracking
DataGalaxy was built in Lyon in 2015 around a specific bet: that a data catalog fails when only engineers can use it, so the interface, glossary and workflows are designed for business analysts and stewards first. It has since added a separate Portfolio product for tracking data and AI initiatives against governance requirements.
- Pricing: Quote only. Quote-only across Starter, Professional and Enterprise catalog tiers, and a separate Portfolio product line. Free plan: none.
- Best for: Business teams that need a usable glossary interface
- Strengths: Metadata glossary; Lineage mapping; Compliance tracking.
Where it falls short
Pricing is entirely quote-only across both product lines, with no published starting figure anywhere on the site. As a mid-sized independent European vendor, it does not have the AI-agent integration depth or the funding scale of the largest US and Singapore-based competitors on this list.
Wrong for
A large enterprise wanting the deepest possible AI-agent integration roadmap, or a buyer specifically wanting a published starting price before any conversation with sales.
Visit DataGalaxy →
#6 erwin Data Intelligence
Governs unstructured data and AI models too · United States · quest.com
Structured + unstructured data AI-model certification Owned by Quest Software
erwin's data-modelling roots go back to 1984, and Quest Software bought the company in October 2021 and still sells it as Quest erwin. The genuine differentiator against the pure-play catalogs on this list: it explicitly governs unstructured data and can certify an AI model's lineage and explainability, not just tag warehouse tables, which matters to a regulated buyer worried about more than structured databases.
- Pricing: Quote only. Quote-only; no published tiers. Free plan: none.
- Best for: Regulated teams needing unstructured-data governance
- Strengths: Automated metadata harvesting; AI-powered stewardship; End-to-end lineage.
Where it falls short
It is a smaller, less AI-agent-focused brand than Atlan or Alation now, with a public profile shaped more by its legacy data-modelling business than by the catalog product itself.
Wrong for
A buyer wanting the newest, most AI-native product on the market, or a team specifically wary of buying a product whose roadmap sits inside a much larger, unrelated software portfolio.
Visit erwin Data Intelligence →
#7 Collibra
The category's largest established incumbent · Belgium / United States · collibra.com
Belgian-founded, 2008 Dual New York/Brussels HQ AI Command Center / Context Engine
Collibra was founded in Brussels in 2008 and is widely credited as Belgium's first software unicorn; its own about page now describes the company as headquartered in both New York and Brussels, and its website terms are governed by New York law.
- Pricing: Quote only. Quote-only; no published tiers. Free plan: none.
- Best for: Large regulated enterprises with a governance office already in place
- Strengths: Data governance policy engine; Business glossary; Automated lineage.
Where it falls short
It is one of the largest, most established names in this category, which is also the trade-off: an incumbent's roadmap and pricing move on incumbent timelines, nothing about pricing is public, and its own dual New York-Brussels structure means it does not cleanly satisfy a strict EU-only procurement requirement.
Wrong for
A small team without a dedicated governance function, who will pay for enterprise policy-engine depth it will not use, and any buyer requiring a vendor genuinely and solely headquartered within the EU.
Visit Collibra →
#8 Microsoft Purview Unified Catalog
Microsoft's metered, Azure-native catalog · United States · learn.microsoft.com
Consumption-based, published rates Governs data, AI models and M365 content together Formerly Azure Data Catalog / Azure Purview
Unified Catalog is the layer of Microsoft Purview where a data product, a business glossary term and the technical tables behind it get connected, sitting on top of Purview's Data Map scanning engine. Pricing is genuinely metered and published rather than quote-only, which is unusual in this category and lets a technical buyer estimate cost without a sales call.
- Pricing: Usage-based. Pay-as-you-go: billed per governed asset per day plus data governance processing units for data-quality and health runs, rates on the Azure pricing page. Free plan: free plan.
- Best for: Organizations already committed to Azure and Microsoft 365
- Strengths: Data Map metadata scanning; Unified business/technical catalog; Data-quality checks.
Where it falls short
It has been renamed twice, from Azure Data Catalog (2016) to Azure Purview (2021) to Microsoft Purview (2022), which makes it easy to find outdated documentation and confuses procurement conversations.
Wrong for
A company with no Azure subscription or Microsoft footprint, or a buyer wanting one catalog that governs every cloud provider equally deeply rather than one built around Microsoft's own stack.
Visit Microsoft Purview Unified Catalog →
#9 data.world
Knowledge-graph catalog, now part of ServiceNow · United States · data.world
Knowledge-graph architecture Now part of ServiceNow Governance + catalog
data.world built its catalog and governance product on a knowledge-graph architecture rather than a flat metadata table, aimed at connecting business meaning to technical assets in a way a simple table-and-tag model does not capture as well. Its own site now states plainly that data.world is now part of ServiceNow, which puts a large enterprise-platform company's resources behind the product.
- Pricing: Quote only. Not published on the current site. Free plan: none.
- Best for: Organizations already committed to ServiceNow
- Strengths: Knowledge-graph metadata model; Business glossary; Data governance workflows.
Where it falls short
As an acquired company, it is no longer evaluated as an independent vendor; expect its roadmap, pricing and packaging to fold into ServiceNow's much larger enterprise-platform sales motion rather than continue as a standalone product with its own pricing page.
Wrong for
A buyer wanting to evaluate a standalone, independently-run catalog company, or anyone not already inside or planning to move onto the ServiceNow platform.
Visit data.world →
#10 AWS Glue Data Catalog
AWS's shared technical metastore · United States · aws.amazon.com
Real published usage pricing Hive-metastore compatible Shared across the AWS analytics stack
The Glue Data Catalog is deliberately narrower than the rest of this list: a technical metadata store, not a business glossary or a stewardship workflow, that Athena, Redshift Spectrum, EMR and Glue's own ETL jobs all read from so a table's schema is defined once. That narrowness is also the honest selling point, alongside genuinely published per-object and per-request pricing rather than a quote.
- Pricing: Usage-based. Published, usage-based: first 1M objects stored free, then $1.00 per 100,000 objects/month; first 1M requests free, then metered; crawlers billed at $0.44 per DPU-hour. Free plan: free plan.
- Best for: Teams standardized on the AWS analytics stack
- Strengths: Hive-metastore-compatible schema store; Automated crawlers; Shared across Athena, Redshift, EMR, Glue ETL.
Where it falls short
It has no business glossary, no stewardship workflow and no approval chain of its own, so it is the wrong tool for a buyer looking for a governance product rather than a shared technical schema store.
Wrong for
A business team looking for a glossary and stewardship interface, or any organization not already running its analytics workloads on AWS.
Visit AWS Glue Data Catalog →
#11 Google Cloud Knowledge Catalog
Google's Gemini-grounded semantic catalog · United States · docs.cloud.google.com
Renamed from Dataplex, April 2026 Gemini-powered semantic context Structured + unstructured coverage
Google's catalog has carried three names: the standalone Data Catalog, deprecated and discontinued on June 1, 2026 in favor of Dataplex Universal Catalog, which Google renamed Knowledge Catalog on April 10, 2026, with the API, client library, CLI and IAM names left unchanged underneath.
- Pricing: Usage-based. Published pay-as-you-go rates: from $0.06 per DCU-hour for standard processing and $0.089 for premium (lineage, quality, profiling), plus metadata storage per GiB. Free plan: free plan.
- Best for: Organizations standardized on Google Cloud and Gemini
- Strengths: Automatic metadata discovery; Lineage across structured and unstructured data; Business glossary.
Where it falls short
The naming churn is a genuine risk: documentation, tutorials and job postings referencing Dataplex are already out of step with the product's current name, which makes evaluating it and finding reliable outside guidance harder than for a stably-named competitor.
Wrong for
A buyer put off by repeated rebranding and naming instability, or any organization not already standardized on Google Cloud for its underlying data estate.
Visit Google Cloud Knowledge Catalog →
Questions and answers
What is the best data catalog software in 2026?
OpenMetadata ranks first of 11, best for teams that want to read the source before trusting it. eccenca Corporate Memory is second (teams wanting explainable, low-code governance) and Atlan third (data teams building AI-agent context). Places 1 to 3 go to challengers, vendors outside the best-known brands, wherever the category has them.
Which vendors in this category are US companies, and does that matter?
Alation, OpenMetadata's commercial operator Collate, erwin Data Intelligence's owner Quest Software, data.world, Microsoft, Google and the company behind AWS Glue Data Catalog are all US-incorporated, which puts customer metadata within reach of US legal process regardless of where the underlying data itself is hosted.
Which of these tools publish real pricing?
Three do.
Is there a free or open-source data catalog?
OpenMetadata is the one genuinely open-source option on this list: free to self-host at any size, with the source code available to read before trusting it with your metadata.
What happened to Zeenea and Castor, two well-known European data catalog vendors?
Both were acquired and no longer operate as independent standalone products.
Which of these tools are open to self-hosting versus hosted-only?
OpenMetadata is the only open-source option that can be self-hosted, and the only one built as open source software from the start.
How is a data catalog different from data governance software?
In practice the two have merged into one product category, and every vendor on this list sells both under one roof, but the distinction is still useful.
Why do Microsoft, Google and Amazon all rank below the independent vendors?
Because their catalogs are the most tied to a single cloud platform of anything on this list: Microsoft Purview bills through an Azure subscription and governs Azure and Microsoft sources most deeply, even though its Data Map can scan AWS, Snowflake and on-premises databases, Google Cloud Knowledge Catalog lives inside Google Cloud, and AWS Glue Data Catalog serves the AWS analytics stack.
Is Collibra a European company?
Partly, and its own materials are explicit about the ambiguity. Collibra was founded in Brussels in 2008 and is widely credited as Belgium's first software unicorn, and it maintains a real Belgian entity, Collibra Belgium BV, for EU privacy purposes.
What should a buyer with no dedicated governance team pick?
Atlan, Alation or DataGalaxy, in that order for this ranking, since all three are built to let a business analyst or steward add glossary definitions directly rather than assuming a governance office will run the rollout.
How often is this data catalog software ranking updated?
Whenever a fact underneath it changes: an acquisition like ServiceNow's purchase of data.world, a pricing change, or a rename like Google's shift from Dataplex Universal Catalog to Knowledge Catalog in April 2026.
