andre-z

8 ms·

31.
by andre-z 3y ago
Qdrant | Rust Engineers, DevOps, Cloud Backend, SRE, ML Engineers, Sales, Marketing | Remote/Berlin/US | full-time | https://qdrant.tech Qdrant is an open-source massive-scale Vector Database. https://github
32.
Google Gemini Embedding Model is there. See how to use(qdrant.tech)
5 points by andre-z 3y ago|1 comments
33.
by andre-z 3y ago
Gemini is a new family of Google PaLM models, released in December 2023. The new embedding models succeed the previous Gecko Embedding Model.
34.
by andre-z 3y ago
See how to use new Gemini Embeddings with Qdrant Vector Database https://qdrant.tech/documentation/embeddings/gemini/
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by andre-z 3y ago
Qdrant is open source. You can run it on your locally. https://github.com/qdrant/qdrant
36.
by andre-z 3y ago
One from the Qdrant team here. We genuinely recommend starting with whatever you already have in your stack to prototype or produce applications with vector search. From the beginning, one should probably not start a new project with a com
37.
Grok is using an open-source Vector Database(twitter.com)
5 points by andre-z 3y ago|2 comments
38.
by andre-z 3y ago
https://github.com/qdrant/qdrant
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by andre-z 3y ago
Real-time data access in Grok is powered by Qdrant, an open-source Vector DB. https://twitter.com/qdrant_engine/status/1721097971830260030 https://github.com/qdrant/qdrant
40.
by andre-z 3y ago
Hello from Qdrant. Would like to hear more about your use case. If not yet connected. https://www.linkedin.com/in/zayarni
41.
by andre-z 3y ago
I'm curious where got the numbers on qps? They are pretty different from our experience. Reached out on LinkedIn. ;)
42.
by andre-z 3y ago
There is on-stage filtering approach with extended HNSW https://qdrant.tech/articles/filtrable-hnsw/
43.
by andre-z 3y ago
Would you say the same about Keyword Search engines like Elastic, Solr, etc? It is just another column type, full-text index, that is available in any proper database. Just a hype...
44.
by andre-z 3y ago
>> Qdrant stores both the vectors and the metadata in a sqlite database. LOL Guys, before developing a DB, learn to write and read code. Qdrant is not using any third party db solutions under the hood (besides Rocks DB for metadata)
45.
by andre-z 3y ago
Made available in Qdrant v1.5 https://github.com/qdrant/qdrant
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by andre-z 3y ago
Why do you thing a test task is a red flag? We hired several people who contributed before.
47.
by andre-z 3y ago
Qdrant | REMOTE | Full-time | https://qdrant.tech | https://github.com/qdrant/qdrant Qdrant is a leading open-source Vector Database provider. We are Looking for Technical Writer, Integrations Engineer, Dat
48.
by andre-z 3y ago
Made possible with Rust and a few optimization tricks. - Qdrant as a vector search engine - ONNX inference in Rust - Embeddings cache & lookup - Parallel & Batch requests - Hybrid search with full-text filtering + vector re-scoring
49.
Qdrant vector db v1.4 released with data visualization UI(github.com)
3 points by andre-z 3y ago|1 comments
50.
by andre-z 3y ago
Qdrant vector database new version v1.4 is out! Besides several improvements in stability, performance, and developer experience, there are also changes in the web UI, including a new visualization feature for vectorized unstructured data.
51.
by andre-z 3y ago
Qdrant https://qdrant.tech | Remote - US Timezone only | Full-time DevOps Cloud Engineer https://join.com/companies/qdrant/8765929-cloud-platform-dev...
52.
by andre-z 3y ago
Likely there are open-source alternatives, also with managed cloud offerings https://github.com/qdrant/qdrant Disclaimer: I’m from the team.
53.
by andre-z 3y ago
I guess because ES/OS are text search engines and not vector databases. Some benchmarks: https://qdrant.tech/benchmarks/
54.
by andre-z 3y ago
Another one, deeper comparison https://www.sicara.fr/blog-technique/how-to-choose-your-vect...
55.
by andre-z 3y ago
Nice try :)
56.
by andre-z 3y ago
It depends on your requirements, for a simple hybrid-search solution, elastic, etc. should be enough. With growing data amount and if working not only with text embeddings, you should try out a dedicated solution, like Qdrant. https:/
57.
by andre-z 3y ago
Awesome! Wouldn't it fit in the 1GB free tier plan? https://cloud.qdrant.io
58.
by andre-z 3y ago
Qdrant, is the most popular, high-performance native vector db, written in Rust https://github.com/qdrant/qdrant (disclaimer: part of the team)
59.
by andre-z 3y ago
Or you can try a proper open-source vector db like Qdrant :) https://github.com/qdrant/qdrant
60.
by andre-z 3y ago
Great! Just, maybe pgvector is not the ideal choice https://news.ycombinator.com/item?id=36713151

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