We used Oden to analyze public data from vendor websites, G2, PeerSpot, Reddit, and AWS Marketplace so you don’t have to. If you’re trying to choose a data catalog platform, you’re probably juggling questions about adoption, governance, AI readiness, and cost. This guide compares Atlan, Alation, Collibra, and Informatica Enterprise Data Catalog (EDC) using only what we can verify from those sources. The goal is to give you a realistic, data-backed picture of where each platform shines and where it may slow you down.

Which data catalog platform has the best rating?

Source for ratings: G2 “Machine Learning Data Catalog” and related product pages, November 2025.

Takeaways

• Atlan has the highest average rating (4.5) and more than 100 reviews, so its score is both strong and reasonably well-sampled.
• Alation and Collibra sit in the 4.2–4.4 band with 80–100+ reviews, suggesting consistently positive but not flawless experiences at enterprise scale.
• Informatica EDC’s 4.3 rating looks competitive, but only 19 reviews means a single large customer can materially move its average; treat it as directional, not definitive.
• G2’s “Value at a Glance” shows median time-to-implement of ~3 months for Atlan versus ~6 months for Alation, hinting that implementation speed is a real differentiator.
• None of these datasets are huge samples by consumer-software standards; you should read recent reviews in your industry and region before making a final call.

How much do data catalog platforms really cost?

Transparent list pricing is rare here, but we do have some concrete reference points from AWS Marketplace, peer reviews, and vendor pricing pages.

Cost patterns (what this means in practice)

• All four are enterprise-priced platforms; even “entry” configurations tend to be mid–five figures per year and climb with users, domains, and modules.
• Collibra and Alation are frequently described by customers as toward the high end of the market, especially when you factor in governance and privacy add‑ons.
• Informatica’s IPU model is attractive if you want to spread spend across multiple IDMC services (catalog, data integration, quality, etc.), but it can be hard to estimate usage upfront.
• Atlan’s own pricing content emphasizes total cost of ownership (implementation effort, automation, and time-to-value) rather than raw license cost, reflecting its competitive stance against legacy catalogs.

Pricing varies significantly by region, usage profile, discounts, and contract length. Always double-check current prices with each vendor's calculator or sales team.

What are the key features of each platform?

Atlan

Core positioning: Active metadata “control plane” for the modern data and AI stack, built by a data team for data teams.

Key Features:

• Active metadata platform that stitches together metadata from warehouses, lakes, BI tools, and orchestration systems to provide unified discovery, cataloging, lineage, and governance across all data assets.
• Cross-system, column-level lineage, including deep integrations with Fivetran and Databricks Unity Catalog, enabling end‑to‑end impact analysis from source systems through BI dashboards.
• Embedded collaboration features (Slack, Jira, Chrome extension) and “Personas/Purposes” personalization to tailor experiences to different stakeholder groups.
• Automation via metadata-driven bots and workflows for quality checks, GDPR classification, and other governance tasks, surfaced through an app/marketplace model.
• Newer modules like Data Quality Studio and an AI-oriented Metadata Lakehouse to support AI governance and trusted metrics at scale.
• Recognized as a leader in Forrester’s Enterprise Data Catalogs for DataOps and in Gartner’s 2025 Magic Quadrant for Metadata Management, underscoring its strength as a modern catalog.

Best For:

• Data platforms built on a modern stack (Snowflake/Databricks/dbt/etc.) that want strong lineage and active metadata automation.
• Organizations prioritizing AI governance and “context for AI agents” over just static cataloging.
• Teams that want collaborative workflows (Slack, Jira) tightly integrated into catalog and governance processes.
• Enterprises looking for faster implementation (G2 median ~3 months) versus heavier, consulting-driven catalogs.

Alation

Core positioning: Data intelligence platform centered on a collaborative data catalog and active metadata graph.

Key Features:

• Powerful search with natural language and ML that surfaces popular and trusted data assets without requiring technical jargon.
• Rich business context: descriptions, terms, definitions, policies, and links to sources, plus trust markers (quality, flags, endorsements, lineage).
• 120+ pre-built connectors across databases, BI tools, files, applications, and AI models, plus an open connector framework.
• Governance capabilities including workflow automation, policy definition, critical data element (CDE) management, and analytics on catalog adoption.
• ALLIE AI for intelligent curation, metadata recommendations, and AI-assisted population of the catalog.
• “Alation Anywhere” to bring catalog context into tools like Excel, Teams, and Slack for in‑workflow discovery and collaboration.

Best For:

• Large enterprises that want an analyst‑friendly catalog with strong search and collaboration.
• Organizations focused on building data culture and literacy, not just technical metadata inventory.
• Regulated industries using the catalog as a backbone for active data governance and regulatory compliance workflows.
• Teams who value mature documentation, training, and a broad ecosystem of integrations.

Collibra

Core positioning: Enterprise-wide Data Intelligence Platform for unified governance of data and AI, with Data Catalog as a central component.

Key Features:

• Unified view of data assets across the enterprise via 100+ native integrations and automated discovery, including unstructured data.
• Strong data product and marketplace concepts, enabling reusable, governed data products with service-level objectives (SLOs) and contracts.
• AI-assisted classification and description generation to speed stewardship and documentation.
• Rich business and technical lineage, including system‑ to column‑level mapping, to support impact analysis and regulatory reporting.
• Embedded policy management, privacy capabilities, and granular access controls to support compliance and ethical AI.
• Recognized as a leader in Forrester and Gartner evaluations for data intelligence and governance platforms.

Best For:

• Global enterprises with complex regulatory obligations (financial services, telecom, healthcare) needing a single governance fabric.
• Organizations standardizing on Collibra for a broad data & AI governance program, not just a catalog.
• Teams that can invest in specialized data stewards and administrators to configure models, workflows, and policies.
• Enterprises already using Collibra for privacy, DSAR, and quality who want catalog as part of the same suite.

Informatica Enterprise Data Catalog / Cloud Data Governance & Catalog

Core positioning: AI-powered “catalog of catalogs” embedded in the Informatica Intelligent Data Management Cloud (IDMC) and broader governance suite.

Key Features:

• Enterprise-scale cataloging that scans and indexes metadata across tens of millions of datasets, including cloud and on‑prem sources.
• CLAIRE AI engine for automated domain discovery, classification, similarity detection, and metadata enrichment.
• End‑to‑end technical lineage with multi-level views (system‑level and granular field‑level) and integration with ETL, BI, and third-party catalogs.
• Integrated data quality rules and scorecards surfaced directly in the catalog, plus support for data provisioning workflows.
• Cloud Data Governance & Catalog service that combines cataloging, governance, quality, and lineage for predictive data intelligence and AI model governance.
• Fits into Informatica’s broader IDMC portfolio (integration, MDM, data quality, marketplace), all purchasable via a unified consumption model.

Best For:

• Enterprises already invested in Informatica (PowerCenter, IDMC, MDM, etc.) that want a tightly integrated catalog and governance layer.
• Organizations with very large, heterogeneous estates (mainframe, on‑prem, multiple clouds) needing an industrial-strength catalog.
• Teams that prioritize deep technical lineage and catalog‑of‑catalogs capabilities over lightweight UX.
• Buyers comfortable with consumption-based pricing and enterprise procurement cycles.

What are the strengths and weaknesses of each platform?

Atlan

Strengths:

• Highest G2 rating in this group (4.5/5) with 121 reviews spanning mid‑market and enterprise customers.
• Users highlight ease of setup (G2 Ease of Setup score ~9.2 vs lower scores for legacy catalogs) and intuitive, Google‑like search for data discovery.
• Reviews frequently praise Atlan’s collaboration features and its ability to make data work “simple” for new hires and cross‑functional teams.
• Strong momentum and analyst validation as a leader in enterprise data catalogs and metadata management, especially for modern data stacks and AI use cases.

Weaknesses:

• Some G2 reviewers say the UI can feel “too technical” for purely business users and that advanced governance concepts (e.g., Personas vs. Purposes) take time to explain.
• Limited UI customization is a recurring complaint, particularly from teams wanting heavier tailoring of the interface.
• As a newer vendor (founded ~2018–2019), Atlan has a shorter legacy footprint than incumbents like Informatica (founded 1993), which may matter for very conservative IT organizations.

Alation

Strengths:

• Strong G2 rating (4.4/5) with 80+ reviews, and widely adopted in large enterprises, including ~40% of the Fortune 100.
• Users frequently call out the intuitive interface, robust search, and collaboration tools for improving findability and trust in data.
• Praised for governance capabilities: connecting technical lineage and data dictionaries with non‑technical documentation and automating regulatory workflows.
• Recognized by TrustRadius and Forrester as a leader in data catalog, collaboration, governance, and metadata management.

Weaknesses:

• Several G2 reviews mention performance issues (sluggishness) on very large datasets and that parts of the UI can be challenging for governance novices.
• Data profiling capabilities are called out as underdeveloped compared with dedicated data quality tools.
• PeerSpot reviewers describe pricing as “moderately expensive” and more costly than expected, especially when you factor in additional governance apps.

Collibra

Strengths:

• Marketed as a complete data and AI governance platform, not just a catalog, with strong coverage of governance, privacy, data quality, and sensitive data discovery.
• G2 users highlight robust features, integrations, and the ability to manage complex AI use cases and compliant, ethical AI workflows.
• Frequently recognized by Gartner, Forrester, and IDC as a leader in data intelligence and governance.
• Well-suited to heavily regulated industries that need detailed lineage and policy enforcement across many domains.

Weaknesses:

• PeerSpot and community feedback note that Collibra is among the most expensive options, with per-user licensing and extra modules driving up total cost.
• A widely upvoted Reddit thread describes Collibra as “extremely difficult to use,” with most users unsure how to find anything, especially compared to newer tools like Microsoft Purview.
• Setup and ongoing configuration can require specialized consultants and resident architects, which adds to time‑to‑value and TCO.

Informatica Enterprise Data Catalog / Cloud Data Governance & Catalog

Strengths:

• G2 reviewers praise Informatica EDC for robust data discovery and metadata management, helping create a comprehensive enterprise catalog.
• AI-driven “catalog of catalogs” concept aggregates metadata from many systems and catalogs, providing a central metadata system of record.
• Deep, multi-level data lineage and strong integration with other Informatica tools (ETL, data quality, MDM, marketplace).
• Cloud Data Governance & Catalog adds policy automation, AI model governance, and unified discovery/governance for data and AI.

Weaknesses:

• G2 reviews describe the tool as resource-intensive and relatively costly, with UI and metadata visibility seen as complex for beginners.
• Compared-side-by-side with newer vendors like Select Star, Informatica scores lower on ease of use and quality of support, even if governance depth is stronger.
• Implementation and tuning often require significant time and expertise, which can slow down adoption for smaller or less mature data teams.

How do these platforms position themselves?

Atlan

Atlan presents itself as “the active metadata platform” and “metadata cloud” that acts as a control plane or “context layer” for AI and analytics, unifying data, meaning, and governance. (atlan.com) It emphasizes bridging the “AI value chasm,” fast time to value, and deep integration with modern data tools like Snowflake, Databricks, and dbt. (atlan.com) Marketing language focuses heavily on AI readiness and active metadata rather than just cataloging.

Alation

Alation calls itself “the data intelligence company” and positions the Alation Data Catalog as the front door to data for both data teams and business users. (g2.com) It leans on being trusted by 40% of the Fortune 100 and frames the catalog as a ML‑powered search engine that underpins self‑service analytics, governance, and AI‑ready data. (alation.com) Its Data Intelligence Project and educational content underscore a narrative around data culture and literacy.

Collibra

Collibra markets a “Data Intelligence Platform” that offers unified governance for data and AI, with Data Catalog, Data Marketplace, and Data Governance as key pillars. (g2.com) Messaging emphasizes trust, compliance, and the ability to manage complex, hybrid data and AI environments via an enterprise metadata graph. (g2.com) Collibra positions itself clearly for organizations with significant governance and AI risk-management challenges rather than lightweight cataloging.

Informatica EDC / Cloud Data Governance & Catalog

Informatica positions its catalog offerings as part of the broader Intelligent Data Management Cloud (IDMC), framing itself as the “enterprise cloud data management leader.” (informatica.com) The Data Catalog and Cloud Data Governance & Catalog pages emphasize AI-powered discovery, a catalog-of-catalogs architecture, and predictive data intelligence tied to governance and data quality. (informatica.com) Messaging targets enterprises that want an integrated stack for integration, quality, MDM, catalog, and governance under one umbrella.

Which platform should you choose?

Below are practical, scenario-based recommendations. Use them as filters alongside your own requirements.

Choose Atlan If:

1. You run a modern data stack (Snowflake/Databricks/dbt/Looker/Tableau, etc.) and want tight, column-level lineage and active metadata across those tools.
2. You care about implementation speed and want to be live in roughly a quarter, not half a year; Atlan’s median time to implement on G2 is around 3 months.
3. You’re prioritizing AI governance and “context for AI agents”—for example, feeding trusted metadata into AI copilots, agents, or LLM-based analytics experiences.
4. Your users are a mix of engineers, analytics engineers, and data-savvy business users who will benefit from Slack/Jira/Chrome integration and collaborative workflows.
5. You want a newer, opinionated platform that automates governance via bots and apps, even if that means less UI customization than legacy tools.

Choose Alation If:

1. Your top priority is an analyst-friendly catalog with powerful search so business users can find data via natural language and popularity-based ranking.
2. You’re building a data culture program and want features that support literacy, collaboration, and stewardship (compose, governance dashboards, education content).
3. You operate at Fortune‑100 / large-enterprise scale and want a vendor with a track record across hundreds of similar customers.
4. You need strong, people-centric governance tooling—linking technical lineage, policies, and ownership with workflows for regulators and auditors.
5. You’re comfortable with premium pricing in exchange for a mature ecosystem and deep support offerings.

Choose Collibra If:

1. You need a single, enterprise-wide governance platform that covers data catalog, privacy, data quality, and AI governance in one suite.
2. Regulatory and risk requirements dominate your roadmap (e.g., Basel, CCAR, GDPR, HIPAA), and you want strong policy, lineage, and access control foundations.
3. You have or can build a dedicated data governance office with stewards and administrators who will configure Collibra’s data models and workflows.
4. Budget is less of a constraint than standardization—you’re willing to pay a premium to have a single, authoritative platform adopted by many lines of business.
5. You’re okay with a steeper UX learning curve if it delivers sophisticated governance and marketplace capabilities for data products.

Choose Informatica EDC / Cloud Data Governance & Catalog If:

1. You’re already an Informatica shop (PowerCenter, IDMC, MDM, Data Quality) and want your catalog and governance to live inside that ecosystem.
2. You manage very large, hybrid estates (on‑prem databases, mainframes, multiple clouds) and need industrial-scale scanning, profiling, and lineage.
3. You value a “catalog of catalogs” that can aggregate metadata from many tools into a single system of record.
4. You have a strong central data team that can handle a more complex UI and configuration in exchange for depth of features.
5. You want to buy catalog, governance, and quality under a unified consumption model (IPUs) and are comfortable forecasting usage and negotiating enterprise contracts.

Sources & links

Company Websites

• Atlan – The Active Metadata Platform
• Alation – Data Catalog & Data Intelligence
• Collibra – Data Catalog Product Page
• Informatica – Data Catalog Overview

Pricing Pages

• Alation Pricing
• Informatica – Consumption-Based Pricing (IPUs)
• AWS Marketplace – Alation Data Catalog
• AWS Marketplace – Informatica Enterprise Data Catalog (Customer Managed Data Platform)

Documentation

• Atlan Help – Trial / Product Tour
• Collibra Documentation – Catalog Features
• Informatica – Cloud Data Governance & Catalog

G2 Review Pages

• G2 – Atlan
• G2 – Alation
• G2 – Collibra
• G2 – Informatica Enterprise Data Catalog
• G2 Comparison – Atlan vs Google Cloud Data Catalog
• G2 Comparison – Informatica EDC vs Select Star

Reddit Discussions

• Reddit – r/MicrosoftFabric thread comparing Purview vs Collibra

Additional Resources

• Atlan – Data Catalog Pricing: Understanding What You’re Paying For in 2025
• Atlan – Active Metadata & Databricks Unity Catalog Integration
• Alation – Data Catalog Product Overview
• Collibra – Data Catalog Key Features
• Informatica – “What Is a Data Catalog?” Article
• PeerSpot – Alation Data Catalog Reviews
• PeerSpot – Collibra Catalog Reviews