Best Collibra Data Quality Alternatives ranked by AI · updated Aug 2026

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Collibra Data Quality combines data quality monitoring with cataloging, governance, and stewardship workflows. It is designed for organizations that want quality issues connected directly to business definitions, ownership, and governance processes.

Developer: Collibra Price: Custom quote 🎯 collibra.com/platform/data-quality

💾 Data Management Data Quality Data Governance data catalog

Top 6 Collibra Data Quality alternatives

Informatica Cloud Data Quality

Informatica

Informatica Cloud Data Quality provides profiling, validation, cleansing, matching, and enrichment for enterprise data across cloud and hybrid environments. It is designed...

Pros

Broad connectivity across enterprise applications, databases, files, and cloud platforms
Strong profiling, parsing, standardization, matching, and enrichment capabilities
Supports centralized data quality rules across hybrid environments

Cons

Typically more expensive and complex to deploy than cloud-native specialist tools
Pricing and packaging are less transparent than open-source alternatives
Requires more administration and specialist knowledge than spreadsheet-oriented tools

Custom quote

Alternatives to Informatica Cloud... → Visit site

Talend Data Quality

Talend offers a data quality solution that combines data profiling, cleansing, and monitoring capabilities.

Pros

Intuitive interface for data quality tasks
Integration with other Talend data tools

Cons

Some advanced features may require additional modules
Support documentation can be limited

Contact for pricing

Alternatives to Talend Data Qualit... →

Soda

Soda is a data quality and observability platform for data teams that need to define, run, and manage checks across data pipelines....

Pros

Offers an open-source execution engine alongside commercial collaboration features
Flexible checks can cover freshness, validity, completeness, and custom business rules
Works across multiple data platforms rather than requiring one warehouse

Cons

Requires more check authoring and maintenance than Anomalo
Soda Cloud pricing is not publicly transparent
The distinction between Soda Core and commercial features can complicate evaluation

Free open source; paid cloud plans contact sales

Alternatives to Soda → Visit site

Great Expectations

Great Expectations is an open-source framework for defining and validating expectations about data. It is used by data engineers to test pipelines,...

Pros

Free and open source for teams that want full control
More customizable validation logic than Comb
Works well in automated pipeline and CI workflows

Cons

More engineering effort to deploy and operate than Comb
Limited built-in observability compared with Monte Carlo
Configuration can become verbose for large test suites

Free, open source; managed services with custom pricing

Alternatives to Great Expectations → Visit site

Ataccama ONE

Ataccama

Ataccama ONE is a data management platform combining data quality, cataloging, governance, observability, and master data management. It serves enterprises that want...

Pros

Combines MDM with data quality, catalog, lineage, and observability
Strong automation for profiling and monitoring data quality
Supports cloud, on-premises, and hybrid environments

Cons

Broader platform scope can mean greater implementation complexity
Identity resolution is less specialized than Verato's core offering
User experience and administration may require trained data-management staff

N/A

Alternatives to Ataccama ONE → Visit site

Precisely Data Quality

Precisely

Precisely Data Quality helps organizations profile, validate, standardize, match, and monitor data across enterprise systems. It is aimed at teams that need...

Pros

Strong matching, validation, and enrichment capabilities for enterprise records
Well suited to customer, product, address, and location-related data
Supports hybrid environments and varied legacy data sources

Cons

Best value often requires adopting additional Precisely capabilities
Pricing is not publicly transparent
Implementation can be complex for smaller data teams

Custom quote

Alternatives to Precisely Data Qua... → Visit site

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