apache/doris is an open-source MPP database that delivers fast SQL analytics, lakehouse query acceleration, and hybrid search across structured, text, and vector data for high-concurrency real-time workloads.
Project overview
The project combines real-time analytics, lakehouse query acceleration, and hybrid search—including AI and vector search—within a single open-source MPP database, making it relevant for teams needing sub-second queries under high concurrency without maintaining separate systems for structured, text, and vector data.
Project type
Evaluation & Observability
Deployment
Refer to project documentation
License
Apache-2.0
Best for
Data teams and AI engineers who need fast SQL analytics and hybrid search across structured, text, and vector data within a single MPP database.
Enterprise teams that require sub-second interactive analytics under high concurrency and may need lakehouse query acceleration.
Key capabilities
Provides streaming ingestion, incremental transformation, and sub-second queries under high concurrency.
Provides SQL-native analytics across JSON, full-text, and vector data for AI and search workloads.
Supports both compute-storage coupled and decoupled deployments. In decoupled mode, stateless compute groups run over shared object storage to scale compute on demand.
Limitations and risks
Some licenses of the third-party dependencies are not compatible with Apache 2.0 License, so you may need to disable some Doris features to comply with Apache 2.0 License.
Before adoption, verify whether features you depend on are affected by the need to disable certain functionality to comply with Apache 2.0 License due to third-party dependencies.
Getting started
Setup difficulty is medium because it requires downloading and installing binaries or compiling from source via Docker. The first success path is to download Apache Doris, then install and configure the cluster.