Top Secoda Alternatives (2026): Data Catalogs Compared & Recommended

Historically, data practitioners have spent 80% of their time managing data, leaving only 20% for the actual analysis, which makes the role valuable. 

A modern data catalog with embedded AI capabilities can fix that.

Secoda connects directly to your data sources, mapping lineage and metadata to deliver context-aware AI that scales with your organization. It was also recently acquired by Atlassian and is now part of Atlassian’s AI and data infrastructure strategy.

This guide covers the top Secoda alternatives, what each does well, and how to find the right fit for you and your team. 🤝

What Should You Look for in Secoda Alternatives?

Before evaluating alternatives, here are the key factors worth considering. 🤖

• Metadata coverage and lineage depth: Look for a platform that tracks column-level lineage across your full data stack, not just surface-level connections between tables
• Data governance capabilities: Prioritize tools that support policy enforcement, access controls, and data governance workflows natively rather than through workarounds
• Search and discovery quality: Evaluate how well the platform surfaces trusted, relevant assets across warehouses, BI tools, and pipelines. Good knowledge management practices make this significantly easier without requiring manual tagging
• Integration with your existing stack: Choose a platform that connects with your current data catalog, transformation, and analytics tools without heavy custom engineering
• Scalability for growing data environments: Ensure the platform doesn’t slow down or break down as your data infrastructure grows
• Deployment flexibility: Consider whether the tool supports your preferred deployment model, whether that is open-source, cloud-hosted, or enterprise-managed

The best alternative is not always the most feature-rich one. It is the one that fits your enterprise data governance maturity, technical setup, and the scale at which your data teams operate.

How to Evaluate Data Catalog Tools During an Acquisition

Before committing to any data catalog tool, here’s what to check. 👇

✅ Pricing and packaging stability: Confirm whether pricing is locked in post-acquisition or subject to change. Some vendors restructure tiers or retire legacy plans after a buyout

✅ Support SLAs: Check whether response times and dedicated technical support availability are contractually guaranteed or informally offered

✅ Export formats: Ensure you can export metadata, lineage maps, and documentation in standard formats so you’re not locked in if you need to migrate

✅ Security and RBAC: Verify that role-based access controls and audit logs meet your compliance requirements, especially if ownership structures are changing

✅ Integration continuity: Confirm that existing connectors and API contracts will be maintained under new ownership and not deprecated without notice

Sorting these out upfront protects you from surprises long after the contract is signed.

Secoda Alternatives At a Glance

Here’s a snapshot of every tool covered in this guide. 📊

Tool	Best features	Best for	Pricing*
ClickUp	AI-powered documentation, Brain, Dashboards, Enterprise Search, Automations	Data teams, enterprises, cross-functional teams	Free Forever; Custom pricing for enterprises
Atlan	Column-level lineage, natural language search, business glossaries, policy management	Data engineers, governance teams, enterprises	Custom pricing
Alation	ML-driven asset discovery, Ask Alation generative AI, behavioral query analysis	Enterprises managing regulated data workflows	Custom pricing
Collibra	Anomaly detection, in-warehouse quality checks, automated ML rules, AI oversight	Enterprises in regulated industries	Custom pricing
DataHub	Natural language metadata queries, end-to-end lineage, fine-grained access policies	Data engineers, open-source teams	Free (open-source)
Amundsen	PageRank-style dataset ranking, automated metadata capture, lineage views	Data engineers, analysts, open-source teams	Free (open-source)
OpenMetadata	Unified metadata graph, no-code lineage editor, role-based access control	Data teams scaling open-source governance	Free (open-source)
Select Star	Column-level lineage, usage insights, auto-generated ER diagrams, dbt sync	Data teams managing warehouse cost and lineage	Custom pricing
Fivetran Catalog	700+ source connectors, schema drift handling, near real-time replication	Data teams managing pipeline automation	Free plan available; Custom pricing
Metaphor	Plain English search, behavioral lineage, social collaboration features	Teams improving data literacy and discovery	Custom pricing

The Best Secoda Alternatives

1. ClickUp (Best for AI-powered data documentation and team collaboration)

Most data catalog tools help you find and govern data. But the surrounding work, like project management, data documentation, cross-team collaboration, and workflow automation, still ends up scattered across separate tools.

ClickUp solves that by bringing it all into one Converged AI Workspace, and works as a knowledge layer that connects your projects, documentation, and AI without context switching.

Here’s what makes ClickUp the best fit for teams: ⬇️

AI-assisted knowledge management with ClickUp Brain

One of ClickUp’s most useful capabilities for data teams is ClickUp Brain, an AI layer that connects tasks, documentation, conversations, and project history into a searchable knowledge system. The AI can summarize documents, generate updates from task activity, and answer questions using information across the workspace.

When managing documentation and governance knowledge, you can ask Brain questions about dataset ownership, previous compliance reviews, or historical decisions tied to specific data assets.

For compliance audits, Brain can pull the status of open audit tasks, flag any unresolved items, and draft a summary without you having to compile it manually.

Enterprise search across tools and data documentation

Large data teams often struggle with knowledge fragmentation.

ClickUp’s Enterprise Search capability addresses this by indexing information across the workspace and connected tools, so teams can find everything they need in one place. The system can retrieve answers from tasks, documents, conversations, and external applications, combining them into contextual responses.

Contextual filtering lets you sort by project, status, or assignee so results stay relevant, and permissions management ensures sensitive governance documents stay accessible only to authorized users.

ClickUp’s security policies enforce role-based access control and audit logs across the workspace, with customer data hosted on AWS under SOC 2 Type 2 certification. With ClickUp’s 100+ Integrations, data from tools like Tableau, Google Sheets, Airtable, etc., flows seamlessly and securely into your workspace.

Documentation and data governance playbooks with ClickUp Docs

Effective data governance requires clear documentation: dataset definitions, governance policies, onboarding guides for analysts, and standard operating procedures for handling sensitive data.

With ClickUp Docs, you get a collaborative environment for building internal wikis and knowledge bases that are directly linked to tasks and workflows.

Teams can create technical documentation, collaborate in real time, convert action items into ClickUp Tasks, and use version history to track how documentation evolves as datasets change over time.

It’s especially useful when engineers and business stakeholders need to stay aligned without relying on internal communication tools that sit outside the work entirely. And for enterprise users, the Docs Hub makes it easy to find the latest version of anything without digging through old chat messages or email threads.

Monitoring governance initiatives with ClickUp Dashboards

Another challenge for data leaders is visibility into ongoing governance work. From compliance initiatives to catalog adoption, efforts often span multiple teams and months of work.

ClickUp Dashboards lets you build customizable reporting views that track everything from project progress and workload distribution to compliance readiness and operational metrics. By consolidating data from tasks, workflows, dependencies, and project timelines, leadership gets a clear view of governance initiatives across the organization.

ClickUp best features

• Assign tasks, update statuses, trigger notifications, or move work across workflows based on predefined conditions automatically with ClickUp Automations
• Build Super Agents in ClickUp that can autonomously generate governance reports, analyze project progress, or surface issues in data management initiatives
• Use ClickUp Chat as a centralized communication layer where teams can quickly convert discussions into actionable items and maintain a traceable history of decisions related to data governance
• Stay on top of billable hours and catch budget risks before they become problems using ClickUp Time Tracking
• Route incoming requests and feedback directly into the right projects using ClickUp Forms, without anyone having to sort through them manually

ClickUp limitations

• High learning curve for new users due to the wide range of features

ClickUp pricing

ClickUp ratings and reviews

• G2: 4.7/5 (11,000+ reviews)
• Capterra: 4.6/5 (4,500+ reviews)

What are real-life users saying about ClickUp? 

A user review says:

2. Atlan (Best for collaborative data workspace and active metadata management)

Atlan connects directly to tools such as Snowflake, dbt, and Tableau to automate lineage, cataloging, and governance in a single collaborative workspace. It continuously updates metadata from connected sources rather than relying on manual input and surfaces context through integrations with Slack and Chrome.

Column-level lineage tracks how data flows from source to final report, supporting impact analysis and debugging across complex environments. AI-powered features generate SQL queries from natural language and automatically keep asset descriptions up to date.

Atlan best features

• Manage and enforce data policies at scale using business glossaries that create a shared vocabulary across technical and business teams
• Extend platform capabilities using 100+ pre-built connectors and an API-first architecture
• Set and track data ownership directly on assets so accountability doesn’t get lost across teams
• Surface downstream impact before making changes using dependency mapping across pipelines

Atlan limitations

• Lineage views and search can feel limited in complex environments
• Learning curve is steep, and some features require extra setup to work effectively

Atlan pricing

• Custom pricing

Atlan ratings and reviews

• G2: 4.5/5 (120+ reviews)
• Capterra: Not enough reviews

What are real-life users saying about Atlan? 

A user review says:

3. Alation (Best for enterprise data cataloging and data governance)

Alation is an AI-powered data intelligence platform that acts as a centralized catalog, enabling organizations to find and trust their data across databases, warehouses, and data lakes.

The platform uses machine learning to analyze actual query behavior and automatically surface trusted assets, keeping the catalog accurate based on real usage rather than manual documentation. It automates data governance, lineage tracking, and metadata extraction, reducing the time teams spend searching for reliable data.

Ask Alation converts plain English questions into SQL or Python instantly, making data accessible to business users without technical expertise. Data Products Marketplace lets teams discover and consume governed data products across the organization, while native integrations with BI tools like Tableau and Power BI keep analysis connected to trusted data.

Alation best features

• Discover trusted data assets faster using ML-driven recommendations based on actual query behavior
• Enforce compliance requirements using automated lineage tracking across cross-system data flows
• Reduce time spent on access requests by giving business users self-service access to governed data products
• Set data quality standards and monitor them directly within the platform without switching tools
• Manage workflows and assign data ownership across assets from one place

Alation limitations

• Performance slows noticeably when navigating large assets
• Data quality and cross-system lineage features have gaps compared to specialized tools

Alation pricing

• Custom pricing

Alation ratings and reviews

• G2: 4.4/5 (90+ reviews)
• Capterra: Not enough reviews

What are real-life users saying about Alation? 

A user review says:

4. Collibra (Best for enterprise-grade data governance and policy management)

An enterprise-grade Data Intelligence Platform, Collibra helps organizations manage and govern data and AI assets at scale. Built on the concept of Data Confidence™, it serves as a centralized system of record, providing business and IT teams with a shared place to discover and certify data across the organization.

Machine learning proactively detects data anomalies, while automated workflows replace scattered spreadsheets and manual compliance processes. It also manages the lifecycle of AI models and agents, ensuring they are built on trusted data and comply with internal and regulatory standards.

Collibra best features

• Monitor pipeline health end-to-end with anomaly detection and rule break alerts across your data cloud
• Generate ML-based data quality rules automatically to catch bad data without manual rule writing
• Oversee AI use cases in production with dedicated monitoring and risk reporting tools
• Automate compliance reporting across regulated data environments without manual data pulls
• Track data lineage at a granular level to support audit requirements and impact analysis

Collibra limitations

• Setup and lineage views can feel complex without dedicated admin support
• Some users reported that the workflow customization options are limited, and learning resources feel incomplete

Collibra pricing

• Custom pricing

Collibra ratings and reviews

• G2: 4.2/5 (100+ reviews)
• Capterra: Not enough reviews

What are real-life users saying about Collibra? 

A user review says:

5. DataHub (Best for open-source metadata management and data discovery)

For data engineers managing complex pipelines and large data ecosystems, DataHub is a good choice. It helps organize and understand data by centralizing metadata across datasets, dashboards, pipelines, and ML models into a single unified view.

The open-source data catalog supports search-based discovery, end-to-end lineage tracking, ownership management, and data quality monitoring. Teams can define data contracts, track PII, and apply governance policies across the data ecosystem.

Originally built by LinkedIn to handle metadata at scale, the tool provides data engineering teams with a flexible foundation they can deploy and extend to fit their own infrastructure, without being tied to a vendor roadmap.

DataHub best features

• Query metadata directly using Ask DataHub to get context-aware answers about datasets, lineage, ownership, and policies
• Track upstream and downstream data dependencies end-to-end across datasets and pipelines
• Sync metadata continuously from diverse data sources using automated ingestion workflows
• Control who can view, edit, or discover specific assets using fine-grained access policies and roles
• Define and monitor data contracts to set quality expectations between producers and consumers

DataHub limitations

• Some users reported that the interface feels clunky, and performance slows with large datasets

DataHub pricing

• Free (open-source)

DataHub ratings and reviews

• G2: Not enough reviews
• Capterra: Not enough reviews

What are real-life users saying about DataHub? 

A user review says:

6. Amundsen (Best for open-source data discovery and search for data engineers)

Amundsen takes a search-first approach to the metadata problem. Its ranking algorithm surfaces datasets based on actual usage patterns rather than how recently someone updated the documentation, so the assets your team already relies on tend to show up first without anyone maintaining a list.

The tool connects datasets to the ETL pipelines, dashboards, and queries that depend on them, giving teams a clearer view of how data flows across the organization. This visibility also helps teams understand where data originates, how it is transformed, and what downstream systems rely on it.

Amundsen best features

• Explore detailed dataset context, including owners, update frequency, and usage statistics in one view
• Visualize upstream sources and downstream dependencies using built-in data lineage views
• Enrich and document datasets collaboratively by adding tags and annotations directly on assets
• Preview table data directly from search results without having to query the source system
• Connect metadata from diverse sources using the Databuilder ingestion framework and its extensible pipeline architecture

Amundsen limitations

• Governance capabilities are limited compared to enterprise-grade platforms
• Performance slows with very large datasets or complex environments

Amundsen pricing

• Free (open-source)

Amundsen ratings and reviews

• G2: Not enough reviews
• Capterra: Not enough reviews

What are real-life users saying about Amundsen? 

A Reddit review says:

7. OpenMetadata (Best for unified metadata management and data observability)

OpenMetadata unifies data discovery, observability, and governance across modern data stacks. It centralizes metadata from pipelines, warehouses, dashboards, and ML models into a single unified graph, breaking down silos across tools like Snowflake, Airflow, and dbt.

The platform supports automated metadata ingestion through 100+ connectors, with built-in lineage tracking, data quality monitoring, and collaboration features. A no-code lineage editor lets anyone on the team map and update data flow visually without filing a ticket. 

Built on an API and schema-first architecture, it is designed to scale across enterprise data environments while remaining accessible to both technical and non-technical users.

OpenMetadata best features

• Search across tables, dashboards, pipelines, and services using keywords, associations, and Boolean-based queries
• Manage permissions for metadata updates, tags, ownership, and lineage using role-based access control
• Monitor data reliability using built-in profiling, quality tests, and freshness checks
• Automate ingestion across your data stack using service connectors and one-click pipelines powered by Airflow
• Set up data tier classifications to prioritize governance efforts across critical versus non-critical assets

OpenMetadata limitations

• Relatively new platform, so community depth and feature maturity lag behind established tools
• Initial setup and integration into existing workflows can require significant customization

OpenMetadata pricing

• Free (open-source)

OpenMetadata ratings and reviews

• G2: Not enough reviews
• Capterra: Not enough reviews

What are real-life users saying about OpenMetadata? 

A Reddit user says:

8. Select Star (Best for automated data discovery and column-level lineage tracking)

Select Star does not ask you to change how your data is stored or managed. It reads your existing infrastructure and immediately starts documenting assets, mapping column-level lineage, and surfacing how data is actually being accessed across your warehouse and BI tools.

A Snowflake cost analysis feature connects data usage directly to warehouse spend, so you can see which assets are driving costs. Continuous DBT sync keeps documentation accurate automatically, and auto-generated entity relationship diagrams help new team members get up to speed without having to track down whoever built the system.

Select Star best features

• Track column-level lineage across integrations with scalable views that are easy to navigate
• Identify unused or redundant datasets by analyzing access patterns across your warehouse
• Automatically detect and map table relationships using query logs without manual configuration
• Keep data asset documentation in sync with your dbt project through continuous automated updates

Select Star limitations

• Advanced reporting and detailed usage insights are limited compared to enterprise-grade alternatives

Select Star pricing

• Custom pricing

Select Star ratings and reviews

• G2: 4.5/5 (50+ reviews)
• Capterra: Not enough reviews

What are real-life users saying about Select Star? 

A user review says:

9. Fivetran Catalog (Best for automated data lineage and pipeline metadata management)

Fivetran is a fully managed, cloud-native data integration platform that automates ELT, moving data from SaaS applications, databases, and files into a centralized data warehouse or data lake without requiring custom engineering fixes.

It handles schema changes, API maintenance, and historical syncs automatically, so pipelines don’t need manual intervention as sources evolve. Security and compliance certifications, including SOC 2, GDPR, HIPAA, and ISO 27001, are included out of the box.

Fivetran Catalog best features

• Ingest data from SaaS apps, databases, and cloud storage using pre-built connectors without writing custom code
• Monitor connector sync health and get alerts when pipelines need attention without manual checks
• Replicate database changes in near real time with minimal load on source systems
• Orchestrate dbt Core transformations directly within Fivetran after data is loaded
• Protect sensitive fields using column-level data controls alongside RBAC and compliance certifications

Fivetran Catalog limitations

• Some connectors have reliability issues, including missing or faulty integrations

Fivetran Catalog pricing

• Free
• Custom pricing

Fivetran Catalog ratings and reviews

• G2: 4.3/5 (770+ reviews)
• Capterra: 4.4/5 (20+ reviews)

What are real-life users saying about Fivetran Catalog? 

A user review says:

Turn Data Chaos Into Clarity With ClickUp

Most data catalog tools do their job and stop there. The documentation still lives in a separate wiki, and the conversations that matter get buried in chat threads nobody goes back to read.

ClickUp closes this gap by connecting the work itself to the documentation, the tasks, and the context around it. So when your team needs answers, they’re already there.

Sign up for ClickUp for free and see what a connected data workflow actually feels like. ✅

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