head to head · open source
Weaviate vs Apache Druid
Weaviate has 16,934 GitHub stars, 1,433 forks, 738 open issues and last shipped yesterday. Apache Druid has 14,093 stars, 3,813 forks, 784 open issues and last shipped yesterday. Weaviate leads on adoption by 20% (16,934 vs 14,093 stars). Weaviate is written in Go under a custom or non-standard licence; Apache Druid is written in Java under Apache-2.0. Weaviate has attracted 8% as many forks as stars, Apache Druid 27%. Weaviate was the more recently maintained of the two, and both are self-hostable with no licence fee.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
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Side by side
| Weaviate | Apache Druid | |
|---|---|---|
| GitHub stars | ★ 17K | ★ 14K |
| License | Custom / other | Apache-2.0 |
| Written in | Go | Java |
| Last push | 2026-11-02 | 2026-11-02 |
| Forks | ⑂ 1.4K | ⑂ 3.8K |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick Weaviate if
- You weight community size — 17K stars and counting
- You want the Custom / other license terms
- Your stack matches Go
- You value the larger contributor base for long-term maintenance
pick Apache Druid if
- You want the Apache Druid feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches Java
- You evaluated both and Apache Druid fits your workflow better
About Weaviate
Weaviate Weaviate is an open source, cloud native vector database that stores both objects and vectors, enabling semantic search at scale. It combines vector similarity search with keyword filtering, retrieval augmented generation (RAG), and reranking in a single query interface. Common use cases include RAG systems, semantic and image search, recommendation engines, chatbots, and content classification. Weaviate supports two approaches to store vectors: automatic vectorization at import using integrated models (OpenAI, Cohere, HuggingFace, and others) or direct import of pre computed vector embeddings…
read the full Weaviate overview →
About Apache Druid
Apache Druid Druid is a high performance real time analytics database. Druid's main value add is to reduce time to insight and action. Druid is designed for workflows where fast queries and ingest really matter. Druid excels at powering UIs, running operational (ad hoc) queries, or handling high concurrency. Consider Druid as an open source alternative to data warehouses for a variety of use cases. The design documentation explains the key concepts. Getting started You can get started with Druid with our local or Docker quickstart. For Kubernetes deployments, the druid operator is maintained in a separate…
read the full Apache Druid overview →
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Frequently asked questions
Is Weaviate or Apache Druid more popular?
Weaviate has 16,934 GitHub stars and Apache Druid has 14,093. Weaviate has the larger community by that measure.
Are Weaviate and Apache Druid free?
Both are open source. Weaviate has no licence declared in this registry, and Apache Druid is licensed under Apache-2.0. Both are free to self-host.
What is the difference between Weaviate and Apache Druid?
Weaviate is written in Go and Apache Druid in Java. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, Weaviate or Apache Druid?
Choose Weaviate if you want the larger community (16,934 stars) or its Custom / other licence terms. Choose Apache Druid if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.