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OpenMLDB

C
C tier on Feature Store SoftwareScore 6.9 · #5 of 17
Android app
Not listed
Free plan
Yes
Runs on
api, Linux, Mac, self-hosted
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Summary

OpenMLDB is a free, open-source machine learning database and feature platform for keeping features consistent between training and inference. It uses SQL to create feature-engineering scripts, deploy them online, and configure online data sources. Its architecture combines real-time and batch SQL engines with a unified execution-plan generator; the documentation says the real-time engine can produce features in a few milliseconds. Extensions such as LAST JOIN and WINDOW UNION add feature-engineering syntax. OpenMLDB offers a cluster version for large production applications and a lightweight standalone version for evaluation and demonstrations. Listed production capabilities include distributed storage and computing, fault recovery, high availability, scale-out, upgrades, monitoring, and heterogeneous memory support. It also provides integrations for importing Apache Pulsar streams and incorporating feature engineering into DolphinScheduler workflows. Kubernetes deployment covers offline and online engines, but the documented cluster setup lacks a TaskManager, so LOAD DATA, SELECT INTO, and offline-related functions are unsupported there.

Who it is for

OpenMLDB may suit teams building SQL-based feature-engineering workflows for machine learning training and inference. The standalone version is intended for evaluation and demonstrations, while the cluster version is aimed at large-scale production applications.

What is good

  • Open source with standalone and cluster versions.
  • SQL workflow covers feature development and online deployment.
  • Real-time engine can produce features in a few milliseconds.
  • Integrations include Pulsar and DolphinScheduler.

What to know first

  • Kubernetes cluster deployment lacks a TaskManager.
  • Some offline-related functions are unsupported in that deployment.
  • Kubernetes tool is tested with Kubernetes 1.19 or later and Helm 3.2.0 or later.

Verdict

OpenMLDB combines SQL feature engineering with real-time and batch execution, and offers both standalone and cluster deployment. Check the documented Kubernetes limitation if you plan to use that deployment path.

OpenMLDB plans and pricing

All plans
OpenMLDB Free Open-source machine learning database; standalone and cluster versions openmldb.ai · 3 Oct 2026

Compared on feature store software

Online store
Yesopenmldb.ai
Offline store
Yesopenmldb.ai
Point-in-time joins
Yesopenmldb.ai
Feature monitoring
Yesopenmldb.ai
Deployment model
self_hostedopenmldb.ai
Serving modes
bothopenmldb.ai

Facts

What it does
OpenMLDB is an open-source machine learning database and feature platform for consistent features in training and inference.openmldb.ai · 3 Oct 2026
SQL workflow
OpenMLDB uses SQL to develop feature engineering scripts, deploy them online, and configure online data sources.openmldb.ai · 3 Oct 2026
Batch and real-time engines
Its architecture includes a real-time SQL engine, a batch SQL engine based on a tailored Spark distribution, and a unified execution plan generator.openmldb.ai · 3 Oct 2026
Real-time features
The documentation says its real-time SQL engine can produce features in a few milliseconds.openmldb.ai · 3 Oct 2026
SQL extensions
OpenMLDB extends SQL for feature engineering with syntax including LAST JOIN and WINDOW UNION.openmldb.ai · 3 Oct 2026
Production capabilities
The documentation lists distributed storage and computing, fault recovery, high availability, scale-out, upgrades, monitoring, and heterogeneous memory support.openmldb.ai · 3 Oct 2026
Deployment options
OpenMLDB has a cluster version for large-scale production applications and a lightweight single-node standalone version for evaluation and demonstration.openmldb.ai · 3 Oct 2026
Pulsar integration
The OpenMLDB Pulsar Connector is described as a way to import real-time data streams from Apache Pulsar into OpenMLDB.openmldb.ai · 3 Oct 2026
DolphinScheduler integration
OpenMLDB provides a DolphinScheduler task for integrating feature engineering into workflows, including offline import, feature extraction, SQL deployment, and online import.openmldb.ai · 3 Oct 2026
Kubernetes deployment
The deployment guide describes Kubernetes deployment for both OpenMLDB's offline and online engines.openmldb.ai · 3 Oct 2026
Kubernetes requirements
The Kubernetes deployment tool is tested with Kubernetes 1.19 or later and Helm 3.2.0 or later.openmldb.ai · 3 Oct 2026
Kubernetes limitation
The documented Kubernetes cluster deployment does not include a TaskManager, so LOAD DATA, SELECT INTO, and offline-related functions are unsupported in that deployment.openmldb.ai · 3 Oct 2026
Spark distribution
The OpenMLDB Spark distribution provides Scala, Java, Python, and R interfaces, and its precompiled AllinOne version supports Linux and macOS.openmldb.ai · 3 Oct 2026
Community support
The project directs users to GitHub Issues for bug reports and feature requests, GitHub Discussions, Slack, and a developer mailing list.openmldb.ai · 3 Oct 2026

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