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Eliza DQ

github.com/se7enquick/eliza-dq
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Category
Developer Tools
Rank
No. 1168Tools index
Pricing
Open Source
Platform
cli
Type
TOOL
GitHub
3 stars
Date

About

Eliza DQ is an open-source Python data quality library that validates data across BigQuery, Athena, Snowflake, Postgres, and other warehouses as well as Polars/pandas dataframes, parquet, and CSV files through a single API and YAML config. Its README publishes benchmarks claiming it beats Soda Core on SQL pushdown speed and cost, and beats Pandera and Great Expectations on large-scale streaming validation (259M rows in under 2 seconds).

What it can do

  • Validate data quality across data warehouses (BigQuery, Athena, Snowflake, Postgres)

    Warehouse tables via YAML/inline config → Data quality check results

  • Validate data in dataframes and files (Polars, pandas, parquet, CSV)

    Dataframe or file (parquet/CSV) → Data quality check results

  • Run built-in data quality checks

    Dataset and check configuration → Pass/fail check results

  • Send data quality alerts

    Check results → Slack message, PDF report, or webhook notification

  • Integrate data quality checks into orchestration pipelines

    Pipeline definitions (Airflow, Dagster, GitHub Actions) → Automated data quality validation runs

Why it made the leaderboard

Gives data engineers one check syntax that runs against a warehouse table, a parquet file, or a DataFrame instead of maintaining separate validation code per source.

Tags

data-qualitypythonpolarssqlbigquerydata-validationdata-engineeringopen-source

Tech Stack

Python

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Editorially curated, with community endorsements as a secondary signal. Corrections welcome.