⚡ World’s Fastest Vector Database for AI & RAG

Casper

Casper is a high-performance Vector Search Database, perfectly suited for high-load search systems and AI applications (RAG). It provides a robust and scalable solution to store, search, and manage vectors efficiently.

Casper is built using Rust 🦀 for performance and reliability.

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Why Casper ?

Casper is the fastest vector database in our internal benchmarks. It consistently outperforms Qdrant across Top@K workloads and both f32 and i8 quantizations. Notably, Qdrant is widely recognized as the leading open‑source engine and demonstrates state‑of‑the‑art throughput versus other databases (e.g., Weaviate, Milvus), as shown in their published results: Qdrant benchmarks. Surpassing Qdrant therefore places Casper ahead of the current open‑source performance leader.

In practice, Casper delivers up to an order‑of‑magnitude higher RPS compared to Qdrant on our datasets, which translates directly into substantial infrastructure savings: fewer CPU cores and instances to achieve the same SLA, lower memory pressure, and reduced total cost of ownership due to more efficient use of compute resources. Casper is the ideal solution for high-load systems, real-time search, and AI & RAG.

Conclusion: Casper achieves performance unattainable for other databases under comparable conditions, requires fewer compute resources at the same load, and materially reduces infrastructure costs through more efficient CPU and memory utilization.

Casper vs Qdrant

Benchmarks RPS & Recall

Hardware:

• CPU: Intel Core i7-13700HX (16 cores / 24 threads)
• Memory: 32 GB RAM

Dataset:

• Vectors: 572,940
• Dimension: 128
• Metric: Inner Product

Qdrant configured with quantile 0.99 (for int8), always ram enabled.

F32

Requests per second, RPS

Engine	Top@10	Top@100	Top@1k	Top@10k	Top@100k
Casper	253.19 k	121.80 k	26.03 k	2.600 k	157
Qdrant	8.78 k	7.79 k	2.80 k	168	18
Speedup	28.8x	15.6x	9.3x	15.5x	8.6x

Recall

Engine	Top@10	Top@100	Top@1k	Top@10k	Top@100k
Casper	0.970	0.951	0.940	0.926	0.965
Qdrant	0.996	0.985	0.978	0.982	0.991

I8

Requests per second, RPS

Engine	Top@10	Top@100	Top@1k	Top@10k	Top@100k
Casper	264.20 k	251.80 k	30.81 k	3.747 k	210
Qdrant	11.01 k	7.97 k	3.25 k	189	19
Speedup	23.9x	31.6x	9.5x	19.8x	11.1x

Recall

Engine	Top@10	Top@100	Top@1k	Top@10k	Top@100k
Casper	0.842	0.910	0.927	0.932	0.964
Qdrant	0.892	0.945	0.960	0.974	0.982

PQ

Requests per second, RPS

Engine	Top@10	Top@100	Top@1k	Top@10k	Top@100k
Casper	204.91 k	123.16 k	25.81 k	3.205 k	224
Qdrant	8.12 k	6.53 k	2.75 k	190	18
Speedup	25.2x	18.9x	9.4x	16.8x	12.3x

Recall

Engine	Top@10	Top@100	Top@1k	Top@10k	Top@100k
Casper	0.630	0.697	0.742	0.800	0.766
Qdrant	0.639	0.764	0.834	0.899	0.899

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• Benchmarks Guide — For details on how to reproduce these benchmarks yourself (rps and recall).

HNSW

Casper features a highly efficient HNSW (Hierarchical Navigable Small World) index, providing fast and accurate similarity search.

Metrics

Casper supports multiple distance metrics:

• Euclidean
• L2SQ
• Cosine
• Inner-Product

Quantizations

Quantizations: f32 (full precision), i8 scalar quantization (compressed). Reduces memory footprint and improves search performance.

• F32
• I8
• PQ

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Free Access

Casper is currently completely free. You can use the following free API token to run Casper:

export API_TOKEN=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJleHAiOjE3OTMyOTAzNTMsImZyZWUiOnRydWV9.GxqiVw5kPzmPb25vo2CMOEwnBhjTH_GTAHeDg_nhlIQ

Quick Start

Download and Launch

To quickly get started with Casper, follow these steps:

1. Download the latest release:

wget https://github.com/casper-vdb/casper/releases/download/v0.0.0/casper-x86_64-unknown-linux-gnu.tar.gz

2. Extract the downloaded archive:

tar -xzvf casper-x86_64-unknown-linux-gnu.tar.gz

3. Set API token:

export API_TOKEN=<YOUR_API_TOKEN>

4. Run Casper:

./casper

Now you're ready to use Casper and explore its features!

Docker: Download and Launch

1. Pull the image:

docker pull alexryzhickov/casper:latest

2. Set API token:

export API_TOKEN=<YOUR_API_TOKEN>

3. Run the container:

docker run -d --name casper -p 8080:8080 -p 50051:50051 -e API_TOKEN="$API_TOKEN" alexryzhickov/casper:latest

4. Verify health:

curl http://localhost:8080/health

API Documentation

Casper exposes an HTTP & GRPC API for managing collections, indexing (HNSW), inserts/updates/deletes, and search. For full endpoint descriptions and curl examples, see the documentation:

• API Docs

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Features

• Advanced Vector Search: High-speed retrieval for complex AI-driven applications.
• Scalability: Designed to handle large-scale data with ease.
• Robust and Reliable: Built in Rust for high performance even under heavy loads.

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