
Qdrant
Weaviate
Milvus
Vespa.ai
Pinecone
ElasticSearch
Zilliz
Algolia
Quickwit
Tantivy
Typesense
OpenSearch
ElasticSearch
Apache Solr
Algolia
Meilisearch
Qdrant is a leading open-source high-performance Vector Database written in Rust with extended metadata filtering support and advanced features. It deploys as an API service providing a search for the nearest high-dimensional vectors. With Qdrant, embeddings or neural network encoders can be turned into full-fledged applications. Powering vector similarity search solutions of any scale due to a flexible architecture and low-level optimization. Qdrant is trusted and high-rated by Machine Learning and Data Science teams of top-tier companies worldwide.
Qdrant
QuickwitQdrant's answer
Advanced Features, Performance, Scalability, Developer Experience, and Resources Saving.
Qdrant's answer
Highest performance https://qdrant.tech/benchmarks/, scalability and ease of use.
Qdrant's answer
Qdrant is written completely in Rust. SDKs available for all popular languages Python, Go, Rust, Java, .NET, etc.
Based on our record, Qdrant should be more popular than Quickwit. It has been mentiond 64 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
If you build on the JVM and want to use Qdrant, the official client is io.qdrant:client โ and it's built for Java. Every call returns a ListenableFuture, requests are assembled with protobuf builders, and it drags a gRPC/Netty stack onto your classpath. From Kotlin, that means fighting the language:. - Source: dev.to / 20 days ago
The stack runs on Qdrant for vector storage, Ollama for local embeddings, and optional Neo4j for a knowledge graph that I added later. I also set it up to route different operations to the best LLM for each task. It provides eleven tools for your Claude Code instance to manage long-term memory operations, and your memories data never leaves your machine. - Source: dev.to / 6 months ago
Qdrant: Open-source vector database optimized for hybrid search and easy integration with ML workflows. - Source: dev.to / 9 months ago
Yes, Java SDKs are critical. But you don't need to rebuild entire orchestration engines just to write agents in Java. The ecosystem already has platforms solving the hard problems: memory (Zep, Mem0, LangMem), tools (specialized platforms), vectors (Pinecone, Weaviate, Qdrant), observability (LangSmith, Helicone, Langfuse). Integrate, don't rebuild. - Source: dev.to / 9 months ago
James Allsopp adds, "LangChain or LlamaIndex for managing LLM workflows, especially if you're adding vector search or documents." These tools handle multi-step processes, essential for complex apps. - Source: dev.to / 12 months ago
Nice... it's cool to see how different companies are putting together best fit solutions. I'm also glad that they at least started out with off the shelf apps instead of jumping to something like a bespoke solution early on. Quickwit[1] looks interesting, found via Tantivity reference. Kind of like ES w/ Lucene. 1. https://github.com/quickwit-oss/quickwit. - Source: Hacker News / about 1 year ago
Https://github.com/quickwit-oss/quickwit to_tsvector in PG never worked well for my use cases SELECT * FROM dump WHERE to_tsvector('english'::regconfig, hh_fullname) @@ to_tsquery('english'::regconfig, 'query'); Wish them to succeed. Will automatically upvote any post Tantivy as keyword. - Source: Hacker News / about 2 years ago
We tested S3 Express for our search engine quickwit[0] a couple of weeks ago. While this was really satisfying on the performance side, we were a bit disappointed by the price, and I mostly agree with the article on this matter. I can see some very specific use cases where the pricing should be OK but currently, I would say most of our users should just stay on the classic S3 and add some local SSD caching if they... - Source: Hacker News / over 2 years ago
Quickwit (https://quickwit.io/) | Paris, France | Onsite and remote (based in Europe) | Full-time The company is fully remote but we also have a small office in Paris. We prefer candidates based in Europe but can make exceptions for the right profiles. - Senior Software Engineer 80-110kโฌ + 0.25-1% equity based on experience.- Source: Hacker News / almost 3 years agoWeโre looking for a senior software engineer to contribute to...
- Another nice comment seen on HN ยซ it seems to be very easy to run, not very IO intensive, and running fine on a single node with modest hardware with >2 billion log rows. It has a really cool dynamic schema feature too.ยป [9] Fun fact: at least 4 users are using Garage[10] as the object storage, this OSS project looks really promising and made the HN front page a few months ago[11], we really cherish the OSS for... - Source: Hacker News / about 3 years ago
Weaviate - Welcome to Weaviate
Tantivy - ๐ On average 2x faster than Lucene ๐ Full-text search โ๏ธ Configurable tokenizer (stemming available for 17 languages) ๐ Tiny startup time (<10ms) โจ๏ธ Natural and Phrase Queries ไทด Range Queries ๐ Incremental Indexing ๐จ Multi-threaded Indexing ๐ฉ JSON Fโฆ
Milvus - Vector database built for scalable similarity search Open-source, highly scalable, and blazing fast.
Typesense - Typo tolerant, delightfully simple, open source search ๐
Vespa.ai - Store, search, rank and organize big data
OpenSearch - OpenSearch is a community-driven, open source search and analytics suite derived from Apache 2.0 licensed Elasticsearch 7.10.2 & Kibana 7.10.2. It consists of a search engine daemon, and a visualization and user interface, OpenSearch Dashboards.