Sphinx Search Reviews

Qdrant Reviews

Sphinx Search mentions (10)

• Best 5 Ecommerce Search Engines for Developers

  Sphinx is a search engine that can be integrated into a website to provide advanced search functionality such as full-text, Boolean, and faceted search. It is a powerful open-source search engine that can handle large amounts of data and quickly return results. - Source: dev.to / over 1 year ago

• Question about embedding for search vs clustering applications

  Have been using Sphinx. It does some processing around suffixes, tenses, and so on, and looks at word proximity (BM25), but is definitely limited. Source: over 1 year ago

• grep like search with preprocessing

  Lucene is the thing you think you need. Elastic Search is a nice wrapper for it. But these are Java, so maybe you want Sphinx Search (C++) or MeiliSearch (Rust). Source: over 1 year ago

• Search MySQL table for multiple keywords and return number of occurrences for each keyword per row

  Using a natural language search will almost certainly be a better solution and PHP may not be the best tool for this task. Figure out how you are going to get the text out of the PDF and where you are going to put it. Look at things like sphinx and full text search in boolean mode for doing the keyword matching. Source: almost 2 years ago

• How to do a Scryfall-like search?

  In practice though you don't do any of this, you get a library to do it for you. I've used Sphinx Search in the past for some fairly hefty (In the order of terabytes), and there's a good book covering how to get it all set up and started. Source: almost 2 years ago

Qdrant mentions (39)

• How to Build a Chat App with Your Postgres Data using Agent Cloud

  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 / 21 days ago

• Hindi-Language AI Chatbot for Enterprises Using Qdrant, MLFlow, and LangChain

  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

• Boost Your Code's Efficiency: Introducing Semantic Cache with Qdrant

  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 1 month ago

• Ask HN: Has Anyone Trained a personal LLM using their personal notes?

  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

• Open-source Rust-based RAG

  There are much better known examples, such as https://qdrant.tech/ and https://github.com/lancedb/lancedb. - Source: Hacker News / 3 months ago