schema-drift

A SQL transformation engine that type-checks your whole pipeline and catches breaking changes before they run — branches, replay, column-level lineage, compile-time contracts, per-model cost. Adapters: Databricks, Snowflake, BigQuery, DuckDB. Single static Rust binary. Apache 2.0.

CI-native security testing for MCP servers. Attack simulation, schema drift detection, and health scoring before agents depend on them.

Dex is the agent-native analytics engineering toolkit. Point it at your warehouse and your dbt project. It learns the landscape, authors your transformations, and tells you exactly what to fix when the schema drifts. Built for analytics engineers and data engineers who want more out of their coding agent.

A deep-dive analytics article on why most KPI “trends” are actually measurement artifacts. Covers the fake-trend taxonomy (schema drift, coverage loss, time shifts, backfills, dedupe, sampling, mix change), a Trend Courtroom evidence protocol, segment invariance tests, and copy-ready checklists + a Trend Report Card for decision safety.

A resilient, fault‑tolerant telemetry analytics pipeline designed to validate, benchmark, and stress‑test high‑frequency sensor data streams under real‑world failure conditions. Includes chaos testing, DLQ repair, GPU‑accelerated ingestion, and end‑to‑end reliability validation for motorsport‑grade telemetry environments.

RL-guided ETL remediation agent with schema-drift detection, error classification, Q-learning decisions, synthetic benchmarks, and AWS Lambda deployment templates.

ValidateLite: A lightweight CLI for database schema validation and data quality checks. Ideal for CI/CD, ETL, and data pipelines.

Schema drift detection for MCP servers. The lockfile MCP should have shipped with.

Drift detection for multi-tenant MSSQL

Detect schema drift and breaking contract changes across APIs, databases, and files. OpenAPI deep diff, CI gate, PR comments.

Schema-drift auto-repair agent for DataHub: detects column renames/retypes/drops, computes the true blast radius from column-level lineage, rewrites dbt SQL and Airflow DAG code with sqlglot AST edits, validates every reference against the live catalog, opens a PR, and writes the repair back to DataHub.

A production-grade, resilient Data Lakehouse pipeline with Schema Drift validation, Ingestion Idempotency, SLA telemetry, and automated CI/CD. Built with Python, DuckDB, Parquet, PostgreSQL, dbt, and Docker.

Break noise. Preserve truth. A deterministic semantic reduction engine for structured data — JSON, YAML, CSV, NDJSON, Markdown, PDF. Fingerprinting, entropy, anomaly detection, schema drift, clustering, and AI-ready essence generation. Built in Rust.

mysql-mcp — MCP server connecting Claude Code to MySQL. Supports SSH tunnels, SSL/TLS, and multiple databases. 20 tools for schema introspection, query execution, ERD generation, stored procedures, triggers, and events. Includes CLI for connection management.

Local JSON schema diff CLI + MCP client for API/MCP drift — offline compare_json, hosted monitoring connector for Pro/Team.

Zero-dependency Python library for data pipeline observability — audit trails, schema drift detection, and row-level change tracking.

Profile CSV, Parquet, JSONL, Avro and SQLite datasets online - infer JSON Schema, detect drift, anomalies, nulls and cardinality.

A schema contract guard for data pipelines. Detects, classifies, and reports schema changes in PostgreSQL databases.

Schema-on-read toolkit for ingesting XML sources with structural drift into a lakehouse architecture.

Detect API schema drift before your integrations break.