OpenMLDB

Input—per 1M tokens

Output—per 1M tokens

Context—tokens

WeightsClosed

About

OpenMLDB is ranked #8 of 15 in feature store software on Inferse. It runs on API, Linux, macOS, Self-hosted. There is a free plan.

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