Can Great Expectations integrate with my existing data pipelines?

Yes, Great Expectations is designed for seamless integration with popular data orchestration tools. It supports various data sources, including SQL and NoSQL databases, making it adaptable to most existing data pipelines for continuous data validation and quality checks.

Is Great Expectations a free tool for data validation?

Yes, Great Expectations is a completely free, open-source data quality validation framework. It provides robust features for data validation through customizable expectations, automated documentation, and data profiling without any cost, making it accessible for all data professionals.

Great Expectations

Data validation testing framework for pipelines

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Shyft Score

Directory quality rating

Verified

73/100

Quiet

Our take

The verdict on Great Expectations

AI-generated

Great Expectations is a powerful open-source tool for data validation and profiling, ideal for teams that need customizable data quality checks without vendor lock-in.

Strengths

Free and open-source
Customizable data validation
Supports SQL and NoSQL databases

Limitations

Lacks real-time monitoring
No AI agent support

Best for: Data teams needing open-source data validation and profiling

Try Great Expectations's free tier to see if it fits your workflow.

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Benefits

Why teams choose Great Expectations

Reduce time spent on data cleaning and validation

Improve data reliability and trust across teams

Automate documentation for better data understanding

Catch data quality issues early in the pipeline

Ensure consistent data quality across multiple sources

About

What is Great Expectations?

Great Expectations is an open-source data quality framework that validates data pipelines through testable expectations. Define checks as code, run them continuously against production data, and get documentation and data profiling reports. Used by data engineers to prevent bad data from reaching ML models and dashboards.

Key capabilities

Data validation through customizable expectations

Automated documentation generation

Data profiling capabilities to understand data distributions

Integration with popular data orchestration tools

Support for various data sources including SQL and NoSQL databases

At a glance

What you can do with Great Expectations

Continuous data quality validation in production pipelines

Pre-model validation to ensure ML training data integrity

Automated anomaly detection in real-time data feeds

Data governance and compliance documentation

Best for

Data engineersData scientistsData analysts

Pricing

Great Expectations pricing

Great Expectations starts at $0

Starting at $0

Ecosystem

Connected ecosystem

MCP servers, AI skills, and integrations that work with Great Expectations

Integrations

Apache AirflowdbtSnowflakeAmazon RedshiftGoogle BigQueryPostgreSQLMySQLPandasApache Spark

FAQs

Frequently asked questions

Common questions about Great Expectations and its capabilities

Great Expectations is an open-source data quality validation framework that helps data engineers, scientists, and analysts ensure data quality. It allows you to define 'Expectations' (assertions about your data) to validate data, generate automated documentation, and profile data distributions, integrating with various data sources and orchestration tools.