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ScyllaDB vs Alopex DB
ScyllaDB shard-per-core design, compatibility with Apache Cassandra and Amazon DynamoDB, and where vector search runs, compared with Alopex DB.
Updated: Oct 15, 2026
What ScyllaDB is
ScyllaDB is a real-time big data database that is API-compatible with Apache Cassandra and Amazon DynamoDB. It is written in C++ on the Seastar framework with a shared-nothing design.
How it works
- Shard per core: it runs a shard on each CPU core of a server, putting every core to work in parallel.
- Ring: much of its distributed design comes from Apache Cassandra, with token ranges spreading data across nodes.
- Raft: schema changes and cluster topology are managed through Raft consensus.
Main features
- Predictable low latency and high throughput.
- CQL plus Alternator, an Amazon DynamoDB-compatible API.
- Change data capture.
Limits
ScyllaDB vector search runs on dedicated vector search nodes separate from the main storage engine, and is documented in the ScyllaDB Cloud docs. Full-text search is offered in ScyllaDB Cloud. The license has moved from open source to source-available.
How it differs from Alopex DB
Both split data across nodes and use Raft consensus.
Alopex DB is a Rust database with vector search and full-text search built into the core engine. ScyllaDB focuses on serving huge volumes of reads and writes at low latency; Alopex DB focuses on combining SQL table rows, vectors and full-text search in a single query. It starts embedded and grows to a cluster on the same engine.
Searching SQL rows and vectors in one query is quick to try in the quickstart. See it for yourself in Alopex DB.
References
- ScyllaDB (GitHub), Shard-per-core Architecture, ScyllaDB Ring Architecture, Raft Consensus Algorithm in ScyllaDB, Vector Search, Vector and Text Search, Why We’re Moving to a Source Available License, Alopex DB (GitHub)