#6 · Primary category: Vector Databases
doris
Apache Doris is a real-time analytics and hybrid search database for AI agents.
Project last updated:08/29/26
GitHub Stars
15.8K
Forks
3.9K
Contributors
829
License
Apache-2.0
Why we included this project
Most RAG and agent projects end up running two databases: a vector store for embeddings and an analytics engine for structured data. Doris collapses that into one SQL engine that does vector, full-text, and JSON search alongside real-time analytics, so a single query can pull semantically similar rows and aggregate business metrics at the same time. The search features sit on top of a mature shared-nothing OLAP core that has been serving sub-second dashboards and warehouse workloads for years, which means they are not a toy feature bolted onto an unproven base. If you already use Doris for reporting, you can adopt the vector capabilities without standing up a second stack.
Articles for this project
No articles for this project yet.
To suggest a topic or contribute an article, contact us.
Related projects in this category
supabase
The Postgres development platform. Supabase gives you a dedicated Postgres database to build your web, mobile, and AI applications.
tidb
TiDB is built for agentic workloads that grow unpredictably, with ACID guarantees and native support for transactions, analytics, and vector search. No data silos. No noisy neighbors. No infrastructure ceiling.
milvus
Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search
qdrant
Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
chroma
Search infrastructure for AI