Asopitech VS
Weaviate vs Alopex DB
Weaviate shards, object store, inverted and vector indexes, and its embedded mode, compared with Alopex DB.
Updated: Oct 13, 2026
What Weaviate is
Weaviate is an open source vector database designed to store and index both data objects and their vector embeddings. It searches by both semantic similarity and keywords.
How it works
- Indexes and shards: each class in the schema creates an index, and an index is made of self-contained shards. Shards can be spread across multiple server nodes.
- Inside a shard: a key-value object store, an inverted index and a vector index. The vector index is a custom implementation of HNSW.
- Writes: each write is persisted immediately and tolerates application and system crashes.
Main features
- Hybrid search that combines semantic similarity and keywords.
- A backend for RAG that retrieves context with vector search.
- Objects and vectors can be updated or deleted even while reads are running.
Limits
Weaviate usually runs as a stand-alone server that clients connect to. Embedded Weaviate, which starts from application code, is marked experimental in the official documentation, with APIs and parameters that may change.
How it differs from Alopex DB
Both keep data and vectors in one place and search by vector similarity.
Alopex DB is a Rust database that grows from embedded to server to cluster on the same engine. It handles SQL, vector search, graphs and KV in one engine. Vector similarity and SQL conditions go in the same query, and table rows and vectors are updated in the same transaction. Start embedded and grow to a cluster on the same engine.
We recommend Alopex DB for writing vector search and SQL in the same query. See it work in the quickstart.