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Embedded graph database — Cypher queries, no server, no subscription. Rust-native with Python, Node.js & Ruby bindings.

54 starsRust

SparrowDB, SQLite of graph DB, written in Rust, Cypher compatible

Name: SparrowDB, SQLite of graph DB, written in Rust, Cypher compatible
Availability: InStock
Author: ryaker

by ryaker·Apr 2, 2026·2 points·1 comment

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AI Analysis

●●●BangerZero to OneBig BrainWizardry

SQLite for graphs—embedded Cypher DB with 93x faster COUNT than Neo4j.

Strengths

•No server, no JVM, no Docker—links directly into your process like SQLite.
•93x faster on global COUNT, 44x faster on Top-10 by degree than Neo4j.
•Built-in MCP server, Bolt protocol, and XChaCha20 at-rest encryption.

Weaknesses

•Traversal queries lag behind warmed Neo4j servers—author admits this openly.
•Pre-1.0 status means API stability and ecosystem maturity still developing.

Post Description

SparrowDB is an embedded Cypher graph database written in Rust. It links into your process the way SQLite does.

I built it because I wanted a graph DB without running Docker or a cloud instance.

SparrowDB kicks butt at point lookups, global COUNT(*), and top-10 by degree but lags on traversals (1-hop, 2-hop, and variable-length paths).

It's an embedded engine with no parallel execution vs a warmed JVM server with a mature query planner. The traversal workload is not the target. Agents, CLIs, serverless functions that need a knowledge graph without provisioning one, that's the target.

Cold start is ~27ms. If you're in a serverless context where Neo4j's startup time is disqualifying, that matters.

Bindings for Python, JavaScript/Typescript, and Ruby. All open the same on-disk format. Built-in MCP server for Claude Desktop. A Bolt protocol server was just added, so gdotv and other Bolt clients can connect. At-rest encryption with XChaCha20-Poly1305. MIT.

https://sparrowdb.dev Demo: https://www.loom.com/share/0dffc9274f5f4338878fe0ffa61f0f4e

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