Typesense VS Weaviate

Typesense Reviews

Weaviate Reviews

Typesense mentions (52)

• FlowDiver: The Road to SSR - Part 1

  Disregarding props-drilling technique in favor of a more reliable and elegant solution we looked for inspiration elsewhere. Another project of ours .find was using Typesense/Algolia components, which looked a bit like black-box/magic, but at the same time provided a clean approach to build complex and highly customizable solutions. - Source: dev.to / about 20 hours ago

• Open Source alternatives to tools you Pay for

  Typesense - Open Source Alternative to Algolia. - Source: dev.to / 5 months ago

• DNS record "hn.algolia.com" is gone

  If you like your penny take a look at Typesense https://typesense.org/ - nothing to complain here. Especially nothing complain about pricing. - Source: Hacker News / 7 months ago

• Obsidian Publish full text search

  I haven’t used Publish, but I’d assume you could use something like https://typesense.org/ to index and search the vault. Source: 10 months ago

• DynamoDB search options

  A cheaper option would be to use https://typesense.org. You can use DynamoDb streams to automatically load records. It has worked well for me. Source: 12 months ago

Weaviate mentions (28)

• How to choose the right type of database

  Weaviate: An open-source, cloud-native vector database built for scalable and fast vector searches. It's particularly effective for semantic search applications, combining full-text search with vector search for AI-powered insights. - Source: dev.to / 2 months ago

• 7 Vector Databases Every Developer Should Know!

  Weaviate is an open-source vector search engine with out-of-the-box support for vectorization, classification, and semantic search. It is designed to make vector search accessible and scalable, supporting use cases such as semantic text search, automatic classification, and more. - Source: dev.to / 3 months ago

• Qdrant, the Vector Search Database, raised $28M in a Series A round

  Congrats to them! What have your experiences with vector databases been? I've been using https://weaviate.io/ which works great, but just for little tech demos, so I'm not really sure how to compare one versus another or even what to look for really. - Source: Hacker News / 3 months ago

• How Modern SQL Databases Are Changing Web Development - #4 Into the AI Era

  A RAG implementation's quality and performance highly depend on the similarity-based search of embeddings. The challenge arises from the fact that embeddings are usually high-dimensional vectors, and the knowledge base may have many documents. It's not surprising that the popularity of LLM catalyzed the development of specialized vector databases like Pinecone and Weaviate. However, SQL databases are also evolving... - Source: dev.to / 4 months ago

• Make Notion search great again: Vector Database

  To find semantically similar texts we need to calculate the distance between vectors. While we have just a few short texts we can brute-force it: calculate the distance between our query and each text embedding one by one and see which one is the closest. When we deal with thousands or even millions of entries in our database, however, we need a more efficient way of comparing vectors. Just like for any other way... - Source: dev.to / 6 months ago