The Deterministic Context Database

Fix your RAG in 5 minutes. Same query → same context, every time.

6x
Faster
100%
Deterministic
$0
Open Source
$ cargo install avocado-cli
user@avocado-db:~/project
$cargo install avoc

Stop Guessing. Start Knowing.

Traditional vector databases are probabilistic. AvocadoDB is deterministic.

The Old Way

  • ×Random results for same query
  • ×Silent failures in production
  • ×Impossible to debug hallucinations
  • ×Expensive cloud bills
  • ×Complex infrastructure setup

The Avocado Way

  • Bit-exact results every time
  • Guaranteed context window packing
  • Full traceability of sources
  • Free & Open Source (MIT)
  • Single binary, zero dependencies

Why AvocadoDB?

The only database designed specifically for deterministic RAG pipelines.

Lightning Fast

Built on SQLite and highly optimized Rust code. Sub-50ms latency for typical RAG queries.

Deterministic

Same query + same data = same context. No more random hallucinations or flaky tests.

Hybrid Search

Combines vector similarity (HNSW) with keyword search (BM25) for best-in-class retrieval.

Local First

Runs entirely on your machine or server. No API keys, no data leaks, no cloud bills.

Version Control

Track changes to your context data with Git-like semantics. Rollback anytime.

Secure by Default

Your data never leaves your infrastructure. Enterprise-grade security out of the box.

Built for Speed

Optimized Rust core + SQLite storage engine = Blazing fast retrieval.

< 50ms
Query Latency
For 1M+ vectors
10k/sec
Indexing Speed
Documents processed
~150MB
Memory Usage
Idle footprint

How it Works

A deterministic pipeline from raw documents to LLM-ready context.

1. Ingest

Documents are processed recursively. Text is split into semantic spans (20-50 lines) with metadata tracking.

docs/*.md → Spans[]

2. Index

Spans are embedded locally (FastEmbed) and indexed into HNSW (Vector) + FTS5 (Keyword) SQLite tables.

SQLite: vectors + fts

3. Compile

Hybrid search results are fused (RRF), deduplicated (MMR), and packed greedily into the context window.

Query → Context String

The Compilation Algorithm

1. EmbedLocal Model
2. SearchHybrid (Sem+Lex)
3. FuseRRF Scoring
4. DiversifyMMR Re-ranking
5. PackGreedy Knapsack
6. SortDeterministic Key

Why AvocadoDB?

See how we stack up against the giants.

FeatureAvocadoDBPineconeChromaQdrant
Determinism100% (Bit-exact)ProbabilisticProbabilisticProbabilistic
ArchitectureEmbedded (SQLite)Managed CloudClient/ServerClient/Server
StorageLocal FilesystemCloud OnlyLocal/ServerLocal/Server
Setup Time< 1 min (cargo install)~5 mins~2 mins~2 mins
Cost$0 (Open Source)$70+/moFree / EnterpriseFree / Cloud

Simple by Design

No complex SDKs. Just a CLI tool that does one thing well.

Install
cargo install avocado-cli
avocado init
Ingest
avocado ingest ./docs --recursive
# Automatically detects .md, .txt, .pdf
Query
avocado compile "How does auth work?"
# Returns deterministic context window

Seamlessly Integrated With

🦜🔗 LangChain
🦙 LlamaIndex
🦀 Rust
🐍 Python
🐳 Docker

Use Cases

Where deterministic retrieval matters most.

Code Documentation Assistant

Help developers understand large codebases with deterministic answers. Perfect for onboarding and code exploration.

Technical Support Q&A

Build support systems with verifiable, citation-backed answers. Reduce ticket resolution time with trustworthy context.

AI Agent Memory

Session management for multi-turn conversations. Track context, replay sessions, debug agent behavior.

Research & Knowledge Base

Search technical documentation and research papers. Line-level citations for academic rigor.

Ready to Fix Your RAG?

Get deterministic context in under 5 minutes.

cargo install avocado-cli