DataScreenIQ

Here's the full description for AlternativeTo:

DataScreenIQ is a data quality screening API that sits between your data source and your database. Send any batch of data (JSON, CSV, or files) and get back a verdict — PASS, WARN, or BLOCK — in milliseconds.

Most data quality tools run after the data is already in your warehouse. By the time Great Expectations or dbt tests flag a problem, bad rows have been in production for hours. DataScreenIQ moves the check to the ingest boundary, before storage, before transformation.

Every batch goes through a single-pass column analysis that checks for schema drift (fields added, removed, or changed type), null rate spikes, type mismatches, empty string rates, duplicate detection, outliers via IQR, approximate distinct counts via HyperLogLog, enum/cardinality tracking, timestamp staleness, and row count anomalies. After the first batch, every subsequent batch is compared against a stored baseline to detect drift automatically.

The API runs on Cloudflare Workers and processes data entirely in-memory. No raw payload data is ever stored. Only aggregated statistics like schema fingerprints, null rates, and health scores are retained.

DataScreenIQ includes a Python SDK on PyPI (pip install datascreeniq) with support for JSON, CSV, Excel, and pandas DataFrames. It integrates with Airflow, Prefect, dbt, and any HTTP-capable pipeline.

Free tier includes 500,000 rows per month with no credit card required. Paid plans start at $19/month for 5 million rows.

For the Tags section, use: data quality, data validation, schema drift, ETL, data pipeline, API, data engineering

For Alternatives to, list: Great Expectations, Soda Core, Monte Carlo, Datafold, dbt tests

That last part is key — it's how people discover you when searching "Great Expectations alternative" on AlternativeTo.