Best 30 Data Quality Tools for PostgreSQL (2026)

    Discover the 30 best open-source and managed data quality tools for PostgreSQL: 25 that connect to PostgreSQL and run checks on its data, dbt tests, which run on PostgreSQL through dbt, and 4 that work from its metadata without reading table data. 10 of them are open source.

    By Ari Bajo - Data Engineer turned Writer.

    Updated on November 5, 2026

    Tools list

    Unified Data Quality Tools

    Tools combining data quality, data observability, data lineage, and a data catalog in one product.

    Collate

    Managed agentic data platform built on OpenMetadata that connects to PostgreSQL with a password or IAM auth, reads pg_stat_statements for usage and lineage, and schedules profiler and data quality workflows.

    My Opinion

    Best for PostgreSQL teams that want lineage from pg_stat_statements plus profiling and data quality tests in one catalog.

    OpenMetadata

    Open-source context platform that connects with a password or IAM auth, reads pg_stat_statements for usage and lineage, and schedules profiler and data quality workflows.

    My Opinion

    Best for teams that want a free, self-hosted catalog with lineage, profiling, and data quality tests on PostgreSQL, with Collate as the managed option.

    Bigeye

    Enterprise AI trust platform that connects to PostgreSQL with a read-only role and SELECT grants, then profiles tables to set metrics and thresholds automatically.

    My Opinion

    Best for PostgreSQL teams that want metrics and thresholds set automatically with a read-only role.

    Sifflet

    Data and AI observability control plane that connects to PostgreSQL as a login role, optionally through the Sifflet Agent, reads schema metadata, and runs read-only SELECT queries to compute monitors.

    My Opinion

    Best for PostgreSQL teams that want read-only monitors in a shared observability platform, connecting through an agent if needed.

    Decube

    Data observability, quality, and lineage platform that connects to PostgreSQL with a read-only role with USAGE and SELECT grants, and runs profiling plus freshness, volume, field health, and custom SQL monitors.

    My Opinion

    Best for PostgreSQL teams that want profiling plus freshness, volume, field health, and custom SQL monitors with a read-only role.

    Elementary Cloud

    Managed data and AI control plane by Boomi that connects to PostgreSQL with a user that reads the Elementary schema created by the dbt package plus INFORMATION_SCHEMA metadata and query history, without read access to your tables.

    My Opinion

    Best for dbt-on-PostgreSQL teams that want monitoring from metadata and dbt results, without read access to tables.

    Ataccama ONE

    Agentic data trust platform with data quality rules, observability, a data catalog, lineage, master data management, and a built-in AI agent.

    My Opinion

    Best for large organizations that want enterprise data quality, master data management, and data governance from one vendor.

    SelectZero

    Self-hosted data observability platform with value-level data validation, column-level lineage, a data catalog, and a business glossary.

    My Opinion

    Best for enterprises that cannot let data leave their environment and want one self-hosted tool, deployed with Docker.

    Data Observability Tools

    Tools focusing on detecting data quality issues with data monitors and anomaly detection.

    Monte Carlo

    Data + AI observability platform that connects to PostgreSQL with a read-only role over optional TLS, collects table metadata hourly, and runs custom SQL, metric, and validation monitors.

    My Opinion

    Best for teams that want PostgreSQL monitored next to their warehouses with hourly metadata and SQL monitors.

    Qualytics

    Data quality control layer that connects with the PostgreSQL JDBC driver, reads the information schema, and runs profiling and quality operations on the tables it discovers.

    My Opinion

    Best for teams that want PostgreSQL tables profiled and scanned with inferred data quality checks.

    DQOps

    Open-source data quality operations center that connects with a PostgreSQL user and sslmode, imports schemas and tables, and runs the profiling and monitoring checks it activates on them.

    My Opinion

    Best for teams that want free, self-hosted profiling and monitoring checks on PostgreSQL.

    Metaplane by Datadog

    Data observability platform by Datadog that connects to PostgreSQL with a user in a group granted pg_monitor and SELECT on tables, from allowlisted IPs or through an SSH tunnel.

    My Opinion

    Best for PostgreSQL teams that want monitors with pg_monitor grants, connecting through an SSH tunnel when the database is private.

    Validio

    Agentic data quality and observability platform that connects to PostgreSQL with a stored credential and SSL mode, and validators poll the selected tables on a schedule.

    My Opinion

    Best for teams that want validators polling PostgreSQL tables with strict SSL verification.

    Coalesce Quality

    Data quality product by Coalesce, built on SYNQ, that connects to PostgreSQL as a dedicated user, reads pg_catalog for tables plus row counts and sizes from planner statistics, and needs SELECT only for custom SQL monitors and profiling.

    My Opinion

    Best for PostgreSQL teams that want cheap metadata monitors from planner statistics, reading rows only for custom tests.

    Lightup

    Enterprise data observability platform that connects to PostgreSQL with a role that can query data and metadata, and scans schemas hourly, daily, or weekly.

    My Opinion

    Best for enterprises that want scheduled data quality scans on PostgreSQL schemas.

    DataKitchen

    Open-source data quality testing tools that connects to PostgreSQL with a database user and pushes read-only SQL queries into the database to profile, test, and monitor tables.

    My Opinion

    Best for teams that want free, self-hosted profiling and generated tests on PostgreSQL.

    Acceldata

    Autonomous data and AI platform that connects with a PostgreSQL user, crawls the selected schemas for schema and table assets, and can analyze query logs.

    My Opinion

    Best for enterprises that want PostgreSQL schemas cataloged with query log analysis in a wider reliability platform.

    Elementary OSS

    Open-source dbt package by Boomi that connects to PostgreSQL with a user that reads the Elementary schema created by the dbt package plus INFORMATION_SCHEMA metadata and query history, without read access to your tables.

    My Opinion

    Best for dbt-on-PostgreSQL teams that want monitoring from metadata and dbt results, without read access to tables.

    Anomalo

    Autonomous data quality monitoring platform where AI agents monitor, investigate, and report issues across structured and unstructured data.

    My Opinion

    Best for enterprises that want ML-based monitoring with little rule-writing, including quality checks on unstructured data such as documents.

    FirstEigen DataBuck

    Zero-code data quality software where AI agents auto-discover rules, validate and reconcile data, and score data trust across sources.

    My Opinion

    Best for enterprises in regulated industries that need automated data reconciliations and validations across legacy and cloud sources.

    DQLabs

    AI-native platform combining data observability, data quality checks, and business context, with anomaly detection, end-to-end lineage, and pipeline observability.

    My Opinion

    Best for enterprises that want data quality and observability in one tool, connected to their data catalog and issue management tools.

    Shift-Left Data Quality Tools

    Tools focusing on preventing data quality issues with data contracts, data-diff, and CI/CD.

    Soda Cloud

    AI-native data quality platform built on data contracts that connects to PostgreSQL with a data source of type postgres (optional schema and sslmode) and runs quality scans over that connection.

    My Opinion

    Best for engineers who want PostgreSQL checks and data contracts as code, run in pipelines or CI/CD.

    Soda Core

    Open-source data contracts engine that connects to PostgreSQL with a data source of type postgres (optional schema and sslmode) and runs quality scans over that connection.

    OSStestingcontractspython-native
    My Opinion

    Best for engineers who want PostgreSQL checks and data contracts as code, run in pipelines or CI/CD.

    Datafold

    AI-powered data engineering platform that connects to PostgreSQL with a role that reads all tables and writes to a datafold_tmp schema, where data diffs keep their scratch tables.

    My Opinion

    Best for PostgreSQL migrations and dbt pull requests that need row-level data diffs.

    Data Contract CLI

    Open-source command-line tool for ODCS data contracts that tests PostgreSQL tables with a username and password, taking host, database, and schema from the contract's servers block.

    OSStestingcontractspython-native
    My Opinion

    Best for teams that want PostgreSQL data tested against vendor-neutral ODCS data contracts in CI/CD with one command.

    Entropy Data

    Data product marketplace that syncs PostgreSQL schemas, tables, and views with column metadata as assets on a schedule, with include and exclude filters.

    My Opinion

    Best for data mesh teams that want PostgreSQL tables published as data products, not monitored.

    Data Testing Tools

    Tools focusing on code-based data quality tests and data profiling for SQL tables, files, and DataFrames.

    Great Expectations

    Open-source Python data quality framework that connects to PostgreSQL with add_postgres() and a psycopg2 connection string, then validates tables or SQL queries as batches of data.

    OSStestingpython-native
    My Opinion

    Best for Python engineers who want free, code-first validation of PostgreSQL tables in their pipelines.

    pointblank

    Open-source data validation library by Posit that validates PostgreSQL tables through its Ibis backend, installed with the postgres extra.

    OSStestingpython-native
    My Opinion

    Best for analysts and engineers who want readable PostgreSQL validation reports, starting free in Python.

    Dataprof

    Open-source profiling library with a Rust core that profiles the result of a PostgreSQL query through its postgres feature, loading the result in memory first.

    OSSprofilingrust-native
    My Opinion

    Best for fast, local profiling of PostgreSQL data with quality scores, without a heavy Python stack.

    dbt tests

    Data tests built into open-source dbt Core that run as SQL in PostgreSQL through the dbt-postgres adapter: generic tests such as unique and not_null, custom SQL tests, and unit tests.

    OSStestingdbt-native
    My Opinion

    Best for teams that transform PostgreSQL data with dbt and want free tests next to their models, run in the same CI/CD.

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    By Ari Bajo - Data Engineer turned Writer.

    Frequently Asked Questions

    Do I need a data quality tool for PostgreSQL, or are constraints enough?
    Start with PostgreSQL itself: NOT NULL, UNIQUE, CHECK, and foreign key constraints reject bad rows at write time. A data quality tool covers what constraints cannot: rules across tables or over time, freshness and volume monitoring, anomalies in values that are valid but wrong, and data loaded by tools that bypass your constraints. Most teams need both. Read more on my data quality tool market guide.
    Which open-source data quality tools work with PostgreSQL?
    Soda Core and Great Expectations run checks on PostgreSQL from YAML or Python, dbt tests run through the dbt-postgres adapter, Data Contract CLI tests tables against ODCS data contracts, pointblank validates tables through its PostgreSQL backend, and Dataprof profiles query results. DQOps and DataKitchen TestGen are self-hosted platforms with profiling and monitoring, and OpenMetadata adds a catalog with lineage from pg_stat_statements.
    How can I edit this tools list?
    If you think a tool belongs here or you want to suggest an edit, I would love to hear from you. You can fill out the feedback form or DM on LinkedIn.