OpenMLDB is a free, open-source machine learning database and feature platform designed to keep features consistent between training and inference. SQL is used to build feature-engineering scripts, deploy them online, and configure online data sources. The architecture combines real-time and batch SQL engines with a unified execution-plan generator; documentation says the real-time engine can produce features in a few milliseconds. SQL extensions include LAST JOIN and WINDOW UNION. OpenMLDB offers a cluster version for large-scale production and a lightweight single-node version for evaluation and demonstration. Listed production capabilities include distributed storage and computing, fault recovery, high availability, scale-out, upgrades, monitoring, and heterogeneous memory support. It integrates with Apache Pulsar for importing real-time streams and with DolphinScheduler workflows for offline imports, feature extraction, SQL deployment, and online imports. Kubernetes deployment covers online and offline engines, but the documented cluster setup lacks a TaskManager, so LOAD DATA, SELECT INTO, and offline-related functions are unsupported there. The Spark distribution provides Scala, Java, Python, and R interfaces.
Who it is for
OpenMLDB suits teams that need a SQL-based feature platform for machine learning training and inference. Its standalone version is intended for evaluation and demonstration, while the cluster version targets large-scale production applications.
What is good
- Free and open source.
- SQL workflow covers feature development and online deployment.
- Cluster and standalone deployment options are listed.
- Supports Pulsar and DolphinScheduler integrations.
What to know first
- Kubernetes cluster deployment lacks a TaskManager.
- Some offline-related functions are unsupported in that deployment.
- Kubernetes deployment tool is tested with Kubernetes 1.19 or later and Helm 3.2.0 or later.
Verdict
OpenMLDB brings SQL feature engineering together with online and batch engines, and offers both standalone and cluster versions. Check the Kubernetes limitation if your deployment depends on LOAD DATA, SELECT INTO, or other offline-related functions.
OpenMLDB plans and pricing
All plansCompared on feature store software
- Online store
- Yes
- Offline store
- Yes
- Point-in-time joins
- Yes
- Feature monitoring
- Yes
- Deployment model
- self_hosted
- Serving modes
- both
