Does it support custom validation logic?

Absolutely. You can write 'Custom Expectations' in Python to handle any business logic that isn't covered by the built-in library.

Great Expectations (GX)

Great Expectations (GX) | Find AI List

Overview

Great Expectations (GX) is the leading technical framework for defining, managing, and maintaining data quality across modern data architectures. In 2026, GX remains the cornerstone of the 'Data-as-Code' movement, providing a declarative syntax (Expectations) to define unit tests for data. Its architecture separates validation logic from the compute engine, allowing it to execute seamlessly across Pandas, Spark, and SQL-based environments like Snowflake, BigQuery, and Databricks. GX Cloud, the enterprise SaaS offering, enhances the open-source core by providing centralized management, team collaboration workflows, and native integrations with observability stacks. The tool's unique 'Data Docs' feature automatically generates human-readable documentation from validation results, ensuring that data contracts are transparent and audit-ready. For 2026, GX has expanded its capabilities into LLM evaluation, providing frameworks to validate unstructured data inputs and outputs in RAG (Retrieval-Augmented Generation) pipelines, securing its position as an essential tool for both traditional BI and advanced AI infrastructures.

Common tasks

Data Validation Automated Data Profiling Metadata Documentation Data Drift Detection LLM Output Validation

FAQ

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Is Great Expectations a data observability tool?

GX is a Data Quality framework. While it provides the core validation engine for observability, full observability platforms often include GX as their underlying testing engine.

Does GX move my data to their servers?

No. The open-source version processes data locally on your compute. GX Cloud only stores metadata and validation results, not the actual raw data.

Can I use GX with real-time streaming data?

Yes, GX can be integrated into streaming pipelines like Spark Streaming by validating micro-batches as they arrive.

What is the difference between GX Core and GX Cloud?

GX Core is the open-source Python library. GX Cloud is a managed platform that adds collaboration, a UI for managing expectations, and hosted Data Docs.

FAQ+