Vector Databases: Qdrant for efficient data storage and retrieval. - Source: dev.to / 5 days ago

AgentCloud uses Qdrant as the vector store to efficiently store and manage large sets of vector embeddings. For a given user query the RAG application fetches relevant documents from vector store by analyzing how similar their vector representation is compared to the query vector. - Source: dev.to / about 1 month ago

Great. Now that we have the embeddings, we need to store them in a vector database. We will be using Qdrant for this purpose. Qdrant is an open-source vector database that allows you to store and query high-dimensional vectors. The easiest way to get started with the Qdrant database is using the docker. - Source: dev.to / about 1 month ago

I took Qdrant for this project. The reason was that Qdrant stands for high-performance vector search, the best choice against use cases like finding similar function calls based on semantic similarity. Qdrant is not only powerful but also scalable to support a variety of advanced search features that are greatly useful to nuanced caching mechanisms like ours. - Source: dev.to / about 2 months ago

I'm currently looking to implement locally, using QDrant [1] for instance. I'm just playing around, but it makes sense to have a runnable example for our users at work too :) [2]. [1]. https://qdrant.tech/. - Source: Hacker News / 2 months ago

Fun fact: We've implemented binary embedding search [1] without the need for a specialized vector database. Instead, we create dimensional tokens like 'embedding_0_0', 'embedding_1_0', and so on, and we harness the robust capabilities of Tantivy [2]. We're really satisfied with the exceptional quality and performance this approach yields. Moreover, Tabby remains a single binary, integrating all these components... - Source: Hacker News / 5 days ago

| Hm, I am interested, but I would love to use it as a rust lib and just have rust types instead of some json config... Yes that's how you use tantivy normally, not sure which json config you mean. `tantivy-cli` is more like a showcase, https://github.com/quickwit-oss/tantivy is the actual project. - Source: Hacker News / 20 days ago

Tantivy - a full-text indexing library written in Rust. Has a great Performance and featureset. - Source: dev.to / 4 months ago

By this I presume you mean build a search index that can retrieve results based on keywords? I know certain databases use Lucene to build a keyword-based index on top of unstructured blobs of data. Another alternative is to use Tantivy (https://github.com/quickwit-oss/tantivy), a Rust version of Lucene, if building search indices via Java isn't your cup of tea... - Source: Hacker News / 5 months ago

We also implemented our schemaless columnar storage optimized for object storage. The inverted index and columnar storage are part of tantivy [0], which is the fastest search library out there. We maintain it and we decided to build the distributed engine on top of it. [0] tantivy github repo: https://github.com/quickwit-oss/tantivy. - Source: Hacker News / 5 months ago