4paradigm/OpenMLDB

Health v2 · maintenance only

Adoption not part of the score

1710 stars · 331 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

OpenMLDB is an open-source machine learning database that acts as a feature platform, computing consistent features for both offline training and online inference using SQL. It is written in C++ and designed to reduce the data engineering effort in AI applications.

Use cases

• compute consistent features for model training and online inference
• serve low-latency features for real-time ML predictions
• run SQL-based feature engineering pipelines
• avoid training-serving skew in feature pipelines
• backfill historical features without data leakage
• replace in-house feature platforms with an open-source alternative

When to choose

• you need a feature store with training-inference consistency
• your team wants SQL-based feature engineering
• you need low-latency online feature serving
• you are building real-time ML applications like fraud detection or risk scoring

When to avoid

• you only need a general-purpose OLTP or analytics database
• your features are simple enough for pandas or Spark alone
• you need a fully managed cloud feature store with vendor support
• your stack is not compatible with JVM/Python/C++ integrations

Facets

service · maturity active

database machine-learning etl streaming machine-learning databases self-hosted cloud feature-store feature-engineering in-memory-database mlops training-inference-consistency sql-database sql data-engineering linux docker

Member repositories

For agents

markdown · JSON · MCP: product_card(name="4paradigm/OpenMLDB")