Apache Doris — Real-Time Analytics and Hybrid Search Database

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Apache Doris is an open-source real-time analytics and search database built on an MPP architecture that runs fast SQL queries and searches structured, text and vector data at the same time. Teams pick it when they need to ship sub-second interactive analytics to their customers, build one real-time warehouse across business domains, analyze high-throughput logs, events and metrics with plain SQL, or give an AI agent a single database for vector, full-text and JSON search instead of several systems. Doris handles streaming ingestion, accelerates queries over open table formats such as Iceberg, Delta Lake and Hudi, and connects to upstream data sources, BI tools and observability stacks. It can be deployed with compute and storage coupled or decoupled; in decoupled mode, stateless compute groups run over shared object storage, scale on demand and isolate workloads from each other. The core is written in Java and C++, and the project is developed under the Apache Software Foundation, with prebuilt downloads and a Docker-based build from source. It is a server database rather than an embedded library, so it is overkill for small jobs. It is released under the Apache-2.0 license.