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About

Actian VectorAI DB is a portable, local-first vector database designed for AI systems that need to run close to their data, including edge, on-premises, and hybrid environments. It enables developers to deploy semantic search, retrieval-augmented generation (RAG), and AI-powered applications without relying on cloud infrastructure, avoiding latency, network dependency, and per-query costs. It provides native vector storage and high-performance similarity search using techniques such as approximate nearest neighbor indexing and algorithms like HNSW, allowing efficient retrieval across large embedding datasets while balancing speed and accuracy. It delivers low-latency search directly on devices ranging from laptops to embedded systems like Raspberry Pi, supporting real-time decision-making and autonomous behaviors without a network round-trip.

About

EmbeddingGemma is a 308-million-parameter multilingual text embedding model, lightweight yet powerful, optimized to run entirely on everyday devices such as phones, laptops, and tablets, enabling fast, offline embedding generation that protects user privacy. Built on the Gemma 3 architecture, it supports over 100 languages, processes up to 2,000 input tokens, and leverages Matryoshka Representation Learning (MRL) to offer flexible embedding dimensions (768, 512, 256, or 128) for tailored speed, storage, and precision. Its GPU-and EdgeTPU-accelerated inference delivers embeddings in milliseconds, under 15 ms for 256 tokens on EdgeTPU, while quantization-aware training keeps memory usage under 200 MB without compromising quality. This makes it ideal for real-time, on-device tasks such as semantic search, retrieval-augmented generation (RAG), classification, clustering, and similarity detection, whether for personal file search, mobile chatbots, or custom domain use.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

AI engineers building edge or on-prem applications who need fast, local semantic search and scalable vector data processing without cloud dependency

Audience

Developers interested in a solution providing multilingual embeddings that run offline and respect privacy

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Actian
Founded: 1980
United States
www.actian.com/databases/vectorai-db/

Company Information

Google
Founded: 1998
United States
ai.google.dev/gemma/docs/embeddinggemma

Alternatives

Alternatives

Categories

Categories

Integrations

Cohere
Docker
Gemma 3
Gemma 4
Hugging Face
OpenAI
Raspberry Pi OS

Integrations

Cohere
Docker
Gemma 3
Gemma 4
Hugging Face
OpenAI
Raspberry Pi OS
Claim Actian VectorAI DB and update features and information
Claim Actian VectorAI DB and update features and information
Claim EmbeddingGemma and update features and information
Claim EmbeddingGemma and update features and information