Best 34 Data Quality Tools for Snowflake (2026)

    Discover the 34 best open-source and managed data quality tools for Snowflake: Snowflake's own data quality feature, 4 that can also run inside your Snowflake account, 24 that connect to Snowflake and run checks on its data, dbt tests, which run on Snowflake through dbt, and 4 that work from its metadata without reading table data. 11 of them are open source. Tools built into or for Snowflake come first, then tools that can run inside your Snowflake account.

    By Ari Bajo - Data Engineer turned Writer.

    Updated on November 5, 2026

    Tools list

    Platform-Native Data Quality Tools

    Data quality features built into your data platform or transformation tool, with data tests and data monitors that run where your data already lives.

    Snowflake Data Quality

    Native Snowflake data quality checks built on data metric functions (DMFs) and expectations, scheduled per table, with volume and freshness anomaly detection and AI-suggested checks from Cortex Data Quality.

    testingobservabilitysnowflake-native
    My Opinion

    Best for Snowflake teams on Enterprise Edition that want data quality checks without adding a vendor or moving data.

    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 Snowflake with a read-only key-pair service user, or runs inside your account as a Snowflake Native App on Snowpark Container Services, with monitors and query-log lineage.

    My Opinion

    Best for large Snowflake estates that want ML monitors and lineage, with the option to run inside the Snowflake account as a Native App instead of an external agent.

    Anomalo

    Autonomous data quality monitoring platform that runs inside your Snowflake account as a Snowflake Native App from the Marketplace, using unsupervised ML to monitor tables and object dependencies for lineage.

    My Opinion

    Best for Snowflake teams that want unsupervised ML monitoring deployed as a Native App, so the data never leaves their Snowflake account.

    Metaplane by Datadog

    Data observability platform by Datadog that connects to Snowflake with a read-only user on a dedicated warehouse, or runs queries inside your account as a Snowflake Native App, monitoring the tables it can SELECT.

    My Opinion

    Best for Snowflake teams that want monitors running in minutes, with queries kept inside their account through the Native App, especially if they already use Datadog.

    Acceldata

    Autonomous data and AI platform that connects to Snowflake with a read-only role (key pair, password, or OAuth) and runs lightweight freshness, row count, and profiling queries on a warehouse, plus data quality rules.

    My Opinion

    Best for Snowflake teams that want lightweight monitoring queries and data quality rules under a read-only role, in a wider data reliability platform.

    Qualytics

    Data quality control layer that connects to Snowflake through the JDBC driver with password or key-pair auth, running every query under a granted role and warehouse to profile and scan tables.

    My Opinion

    Best for Snowflake teams that want inferred data quality checks generated from profiles, with every query under one role and warehouse.

    DQOps

    Open-source data quality operations center that connects over JDBC with a Snowflake user (optional warehouse and role) and runs profiling and monitoring checks for volume, freshness, and schema changes on imported tables.

    My Opinion

    Best for teams that want free, self-hosted profiling and freshness, volume, and schema checks on Snowflake tables.

    FirstEigen DataBuck

    Zero-code data quality software that scans each Snowflake data asset in place, computes ML-based data quality metrics and a trust score, and writes them to Snowflake object tags.

    My Opinion

    Best for Snowflake teams that want ML data quality scores written back as Snowflake object tags, with no rules to write.

    Validio

    Agentic data quality and observability platform that connects to Snowflake with a key pair, password, or programmatic access token plus role and warehouse, and runs validators on selected tables or views on a polling schedule.

    My Opinion

    Best for Snowflake teams that want validators with segmentation on selected tables and views, polled on a schedule.

    DQLabs

    AI-native data quality platform that connects to Snowflake to process asset metadata and assess column-level data quality with anomaly detection.

    My Opinion

    Best for Snowflake teams that want column-level data quality scoring and anomaly detection without writing rules.

    Coalesce Quality

    Data quality product by Coalesce, built on SYNQ, that connects to Snowflake with a key-pair service user on an XSMALL warehouse, reads metadata and ACCOUNT_USAGE query logs, and reads rows only for custom monitors and SQL tests.

    My Opinion

    Best for Snowflake teams that want low-cost metadata monitors on an XSMALL warehouse, reading rows only for custom tests.

    Lightup

    Enterprise data observability platform that connects with a Snowflake user to one database, with an optional warehouse and role, and runs scheduled metrics on tables, views, materialized views, and external tables.

    My Opinion

    Best for enterprises that want scheduled data quality metrics on Snowflake tables, views, and external tables.

    Telmai

    AI-based data observability platform that connects to Snowflake with key-pair auth and SELECT, USAGE, and MONITOR grants, and detects anomalies and drift on tables and views, processing the data outside the warehouse.

    My Opinion

    Best for teams that want anomaly and drift detection on Snowflake tables and views, processed outside the warehouse.

    DataKitchen

    Open-source data quality testing tools that connects to Snowflake with key-pair or password authentication and pushes read-only SQL queries into Snowflake to profile, test, and monitor tables.

    My Opinion

    Best for teams that want free, self-hosted profiling and generated tests on Snowflake, with queries kept read-only.

    Pantomath

    Data pipeline observability platform that runs as a Snowflake Connected App that keeps its metadata in Snowflake and joins Snowflake lineage with other platforms in one pipeline view.

    My Opinion

    Best for teams that want end-to-end pipeline lineage across Snowflake and the jobs that feed it, with metadata kept in Snowflake.

    Elementary OSS

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

    My Opinion

    Best for dbt-on-Snowflake teams that want monitoring from metadata and dbt results, without granting read access to table data.

    Unified Data Quality Tools

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

    Sifflet

    Data and AI observability control plane that connects to Snowflake with a read-only service user, reads ACCOUNT_USAGE for lineage, usage, and tags, and offers a Snowflake Native App in private preview.

    My Opinion

    Best for Snowflake teams that want monitors plus lineage, usage, and tags from ACCOUNT_USAGE, with business users in the loop.

    Collate

    Managed agentic data platform built on OpenMetadata that connects with a Snowflake user (password or key pair), reads metadata plus ACCOUNT_USAGE query and access history for lineage, and runs profiler and data quality workflows.

    My Opinion

    Best for Snowflake teams that want a catalog, lineage from query history, and data quality tests in one platform, open-source or managed.

    OpenMetadata

    Open-source context platform that connects with a Snowflake user (password or key pair), reads metadata plus ACCOUNT_USAGE query and access history for lineage, and runs 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 Snowflake, with Collate as the managed option.

    Ataccama ONE

    Agentic data trust platform that connects over JDBC and, with pushdown enabled, runs profiling, data quality evaluation, and monitoring projects directly in Snowflake on the connection's warehouse.

    My Opinion

    Best for enterprises that want profiling and data quality rules pushed down to run inside Snowflake compute, next to governance and MDM.

    Bigeye

    Enterprise AI trust platform that connects to Snowflake with a key-pair service user and warehouse, reads ACCOUNT_USAGE for lineage and metadata metrics, and runs metric queries on granted tables.

    My Opinion

    Best for Snowflake teams that want lineage and metadata metrics from ACCOUNT_USAGE, plus metric queries on the tables that matter.

    Decube

    Data observability, quality, and lineage platform that connects to Snowflake with a key-pair user, role, and warehouse, collects metadata and profiles, and runs freshness, volume, field health, custom SQL, and schema drift monitors.

    My Opinion

    Best for Snowflake teams that want freshness, volume, field health, and schema drift monitors next to a catalog.

    Elementary Cloud

    Managed data and AI control plane by Boomi that connects to Snowflake with a key-pair user created by a dbt macro and reads the Elementary schema, INFORMATION_SCHEMA metadata, and query history, without read access to your tables.

    My Opinion

    Best for dbt-on-Snowflake teams that want monitoring from metadata and dbt results, without granting read access to table data.

    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.

    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 Snowflake with a password, key pair, SSO, or OAuth, and runs scans that execute checks against the configured database, schema, and warehouse.

    My Opinion

    Best for engineers who want Snowflake data contracts and checks in YAML, run in CI/CD or on a schedule against a chosen warehouse.

    Soda Core

    Open-source data contracts engine that connects to Snowflake with a password, key pair, SSO, or OAuth, and runs scans that execute checks against the configured database, schema, and warehouse.

    OSStestingcontractspython-native
    My Opinion

    Best for engineers who want Snowflake data contracts and checks in YAML, run in CI/CD or on a schedule against a chosen warehouse.

    Datafold

    AI-powered data engineering platform that connects to Snowflake with a key-pair service user, reads ACCOUNT_USAGE for discovery, and runs data diff queries in the warehouse, keeping scratch data in a DATAFOLD_TMP schema.

    My Opinion

    Best for Snowflake migrations and dbt pull requests that need row-level data diffs computed inside the warehouse.

    Recce

    AI data review agent for dbt pull requests that connects with a password or key pair, role, and warehouse, and queries Snowflake directly to compare base and current environments in a data diff.

    My Opinion

    Best for dbt-on-Snowflake teams that want to compare dev and prod data before merging a pull request.

    Data Contract CLI

    Open-source command-line tool for ODCS data contracts that tests Snowflake tables against an ODCS data contract with datacontract test, authenticating with a password or a private key set in DATACONTRACT_SNOWFLAKE_* variables.

    OSStestingcontractspython-native
    My Opinion

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

    Entropy Data

    Data product marketplace that connects to Snowflake with a key pair or access token to sync databases, schemas, tables, and semantic views as assets, and writes data contract tags and comments back.

    My Opinion

    Best for data mesh teams that want Snowflake tables published as data products with data contracts, not table monitoring.

    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 Snowflake with add_snowflake() using account, user, warehouse, role, and a private key, 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 Snowflake tables in their own pipelines, without a managed UI.

    pointblank

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

    OSStestingpython-native
    My Opinion

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

    DataComPy

    Open-source DataFrame comparison library from Capital One that compares Snowpark DataFrames or Snowflake tables by name, joining them with EQUAL_NULL inside Snowflake and reporting differences.

    My Opinion

    Best for migration and refactoring work that needs a row-by-row diff of two Snowflake datasets with tolerances.

    dbt tests

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

    OSStestingdbt-native
    My Opinion

    Best for teams that transform Snowflake 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

    Does Snowflake have built-in data quality checks?
    Yes. Snowflake data metric functions (DMFs) measure things like null counts, duplicates, and freshness on a schedule, and Snowflake reports when a value breaks the expectation you set. They run on serverless compute that Snowflake bills separately, and you still define what counts as a problem. Third-party tools add anomaly detection that learns thresholds, lineage to downstream dashboards, incident management, and checks across more than Snowflake. Read more on my data quality tool market guide.
    Which data quality tools run inside Snowflake?
    Monte Carlo, Anomalo, and Metaplane can run inside your Snowflake account as Snowflake Native Apps on Snowpark Container Services, and Sifflet offers one in private preview, so queries and data stay in Snowflake. DataComPy and Ataccama ONE push comparisons and data quality rules down to Snowflake compute. Most other tools connect from outside with a read-only service user.
    How do data quality tools affect Snowflake costs?
    Every check is a query, so it uses warehouse credits. Tools that read metadata from ACCOUNT_USAGE and INFORMATION_SCHEMA, such as Monte Carlo, Sifflet, Bigeye, and Coalesce Quality, can monitor freshness and volume without scanning tables, and Coalesce Quality recommends an XSMALL warehouse. Telmai processes data outside the warehouse. Give the tool a dedicated warehouse so you can see and cap what it spends.
    Which open-source data quality tools work with Snowflake?
    Soda Core and Great Expectations run checks on Snowflake tables from YAML or Python, dbt tests run there through the dbt-snowflake adapter, Data Contract CLI tests tables against ODCS data contracts, DataComPy diffs tables inside Snowflake, and OpenMetadata adds a catalog with lineage and data quality tests. DQOps and DataKitchen TestGen are self-hosted platforms with profiling and monitoring.
    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.