SvectorDB is a powerful serverless vector database designed to simplify the management and retrieval of high-dimensional vectors in various applications.

What makes SvectorDB 'serverless'?

For a product to be truly serverless, it should be fully managed, scale automatically, and charge per request instead of 'scaling units' like capacity. SvectorDB meets all these criteria, making it a truly serverless product.

Does SvectorDB have a free tier?

Yes, you can try SvectorDB for free, with up to 1,000 items in our sandbox tier.

What type of indexes does SvectorDB support?

SvectorDB supports the 3 most common types of indexes: Euclidean, Cosine, Dot Product.

What languages does SvectorDB support?

We offer official clients for JavaScript and Python. We also have a publicly available OpenAPI spec, so you can use any language you like.

How fast is SvectorDB?

From a recent benchmark, queries had a mean latency of 9ms and a median of 8.48ms. The benchmark was conducted on a database with 10,000 items, with a vector dimension of 128, using a Euclidean index. Requests were sent in parallel with batches of 10 queries at a time.

Does SvectorDB support Infrastructure as Code (IaC)?

Yes, SvectorDB has native CloudFormation support. To get started, check out our CloudFormation documentation.

What limits does SvectorDB have?

While almost all limits are adjustable, the default limits are as follows: Reads per second: 100, Writes per second: 100, Items in a single database: 1,000,000.

Who should use SvectorDB?

SvectorDB is designed for developers who want to build applications that require the management and retrieval of high-dimensional vectors. It is particularly useful for applications such as: Recommendation systems, Document similarity search, Image similarity, RAG Chatbots, Embedding nearest neighbour search. Any application that needs to index and retrieve vectors by nearest neighbour can benefit from SvectorDB, whether high or low volume and dimensionality.

Who should not use SvectorDB?

While SvectorDB is a powerful tool, it may not be the best fit for every use case. SvectorDB may not be the best fit for you if: You need to store and retrieve non-vector data, You need fine-grained control over algorithmic parameters such as efConstruction, M, etc, You need a fixed cost each month.

SvectorDB : Avaliações, preços, principais recursos, casos de uso, alternativas

Name: SvectorDB : Avaliações, preços, principais recursos, casos de uso, alternativas
Rating: 5 (8864 reviews)
Author: toolify

Categoria High Revenue AIs GPTs

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SvectorDB

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Introdução:

Create a serverless vector database in under 120 seconds

Adicionado em:

Março 17 2024

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SvectorDB Informações do produto

O que é SvectorDB?

Create a serverless vector database in under 120 seconds

Como usar SvectorDB?

No technical mumbo jumbo, just a few lines of code and you're good to go. Within minutes, you could have a fully managed serverless vector database up and running.

Principais recursos da SvectorDB

RAG chatbot

Document search

Recommendations

Casos de uso da SvectorDB

RAG chatbot

Document search

Recommendations

Perguntas frequentes de SvectorDB

What is SvectorDB?
What makes SvectorDB 'serverless'?
Does SvectorDB have a free tier?
What type of indexes does SvectorDB support?
What languages does SvectorDB support?
How fast is SvectorDB?
Does SvectorDB support Infrastructure as Code (IaC)?
What limits does SvectorDB have?
Who should use SvectorDB?
Who should not use SvectorDB?

SvectorDB E-mail de suporte e contato de atendimento ao cliente e contato de reembolso, etc.

Mais contato, visite a página de contato(https://svectordb.com/contact-us)
SvectorDB Empresa

Mais sobre SvectorDB, visite a página sobre nós(https://svectordb.com/) .
Preço de SvectorDB

Link de preços de SvectorDB: https://svectordb.com/#pricing

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Preço de SvectorDB

Reads

$5 / million

Pay per million reads

Writes

$20 / million

Pay per million writes

Storage

$0.25 / GB

Pay per GB of storage

Para obter os preços mais recentes, visite este link: https://svectordb.com/#pricing

Análise de SvectorDB

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pinecone pricing

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