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Free vector database comparison tool - from Superlinked logo

Free vector database comparison tool - from Superlinked

Free

Open-source inference for the models behind your agents

2
Developer ToolsFreeFree tier
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Saas
Company
Vector DB Comparison
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About Free vector database comparison tool - from Superlinked

Vector DB Comparison is a free and open source tool from VectorHub to compare vector databases. It allows users to compare different vector databases based on various features such as OSS, License, Dev Lang, VSS Launch, Filters, Hybrid Search, Facets, Geo Search, Multi-Vector, Sparse, and BM25.

How to Use

  1. Scroll horizontally to view all attributes. 2. Hover column header to view description and filter. 3. Click on column header to sort, and shift + click to sort by multiple columns. 4. Drag columns next to vendor column to pin them. 5. Hover on cells with info symbol to read comments from maintainers.

Vector DB Comparison's

Key Features

  • Comparison of vector databases
  • Filtering and sorting based on attributes
  • Vendor information and insights

Use Cases

  • Selecting the appropriate vector database for a specific project

Key Features

Comparison of vector databases
Filtering and sorting based on attributes
Vendor information and insights

Pros & Cons

Pros
  • Up to 50x cheaper than using frontier-lab embedding/reranker APIs
  • 2.7x faster inference speed compared to equivalent commercial models
  • 96% accuracy on MTEB benchmarks with Qwen3.6-27B
  • Full data privacy: prompts and documents never leave your cloud
  • Runs on existing Kubernetes infrastructure (AWS EKS, GKE, AKS)
  • Supports air-gapped deployments for security-sensitive environments
  • Open source (Apache 2.0) with strong community support (2.3K GitHub stars)
  • Integrates with major vector databases and agent frameworks (OpenAI SDK, LangGraph, CrewAI)
Cons
  • Requires Kubernetes cluster management and DevOps expertise to self-host
  • No fully managed SaaS tier yet (currently in waitlist phase for managed service)
  • Limited to the 100+ models included; custom model support may require additional work
  • Performance depends on GPU availability and configuration of the cluster

Best For

Selecting the appropriate vector database for a specific project

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FAQ

How does SIE work?
SIE is a Kubernetes inference cluster: a stateless gateway publishes work to a queue, and worker pods pull tasks, form full batches, and share GPUs across many models. It supports auto-scaling, worker pools, and model stacking to optimize resource usage.
Is SIE free to use?
Yes, the self-hosted version is always free. You can run SIE on a laptop via Docker, on a Kubernetes cluster via Helm, or on AWS, GCP, and Azure via Terraform. Superlinked also offers a managed service (upcoming) with free hosted capacity for selected projects through an inference grant application.
What models does SIE support?
SIE supports over 100 small open models including embedding models (bge-m3, gte-Qwen2-7B), rerankers (qwen3-reranker, bge-reranker-v2-m3), OCR models (glm-ocr, paddleocr-vl, docling), structured extraction (gliner2, nuner-zero), guardrails (granite-guardian-2b), and general LLMs (qwen3.6-27b, qwen3.6-4b).