db-benchmarks
qdrant
db-benchmarks | qdrant | |
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24 | 141 | |
111 | 17,943 | |
2.7% | 3.4% | |
4.9 | 9.9 | |
12 months ago | 4 days ago | |
PHP | Rust | |
GNU Affero General Public License v3.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
db-benchmarks
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Dozer vs. AirByte and Elasticsearch: The Fast Lane to Data Serving Efficiency
> I decided to experiment with this setup and the NY Taxi Dataset. The initial goal was to populate ElasticSearch with ~14 million rows, loading data from a compressed parquet file of ~350 MB.
> I tried multiple times, but the operation failed continuously, due to JVM memory constraints
Here's a script https://github.com/db-benchmarks/db-benchmarks/blob/main/tes... which loads 1.7B NYC taxi ride documents into Elasticsearch.
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Meilisearch vs Manticore Search
In general, you are correct about another missing key: since we added an exception for MySQL by including two keys, we should perhaps optimize it to the maximum and add the rest as well. However, it would be better to make this more visible directly within the results then. I've created a task about it https://github.com/db-benchmarks/db-benchmarks/issues/30 . Thank you for pointing this out. If you see more issues, feel free to file them on github.
- Elastic, Loki and SigNoz – A Perf Benchmark of Open-Source Logging Platforms
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ZincSearch – lightweight alternative to Elasticsearch written in Go
> It's interesting to note that Elasticsearch and Opensearch are general purpose search engine, Solr as well. They are all powered by Lucene, the popular and performant search engine library.
Another search engine which can be considered general, is not based on Lucene and is not less powerful than Elasticsearch/Solr is Manticore Search [1]
[1]: https://github.com/manticoresoftware/manticoresearch
> I would love to see some benchmarks by category :)
I'd love too. We started this work on db-benchmarks [2] , hopefully we'll have resources to continue it. Contributions are very welcome. It's 100% opensource [3]
[2]: https://db-benchmarks.com/
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Manticore Search: Elasticsearch Alternative
Comparing full-text search engines on queries that aren't full-text search are of course slow, these tests should be adapted to the proper usage of the tested DBs and not just benchmarked across the board..
Example: https://db-benchmarks.com/?cache=fast_avg&engines=elasticsea...
- No, QuestDB is not Faster than ClickHouse
- Announcing DB Benchmarks - the most fair open source database and search engines benchmarks
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110 million comments from Hacker News benchmark
Clickhouse: no tuning , just CREATE TABLE ... ENGINE = MergeTree() ORDER BY id and standard clickhouse-server docker image.
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1.1 million comments from Hacker News: small data full-text / analytics test
MySQL and Percona Server for MySQL: no tuning , just CREATE TABLE ..., FULLTEXT(story_text,story_author,comment_text,comment_author))and standard mysql docker image .
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Announcing DB Benchmarks - the most fair open source database benchmarks
https://db-benchmarks.com is a platform and a framework for making the most fair, transparent and open source database and search engines benchmarks. No more benchmarketing, because:
qdrant
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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.
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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.
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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/
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Show HN: A fast HNSW implementation in Rust
Also compare with qdrant's Rust implementation; they tout their performance. https://github.com/qdrant/qdrant/tree/master/lib/segment/src...
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pgvecto.rs alternatives - qdrant and Weaviate
3 projects | 13 Mar 2024
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Open-source Rust-based RAG
There are much better known examples, such as https://qdrant.tech/ and https://github.com/lancedb/lancedb
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Qdrant 1.8.0 - Major Performance Enhancements
For more information, see our release notes. Qdrant is an open source project. We welcome your contributions; raise issues, or contribute via pull requests!
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Perform Image-Driven Reverse Image Search on E-Commerce Sites with ImageBind and Qdrant
Initialize the Qdrant Client with in-memory storage. The collection name will be “imagebind_data” and we will be using cosine distance.
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7 Vector Databases Every Developer Should Know!
Qdrant is an open-source vector search engine optimized for performance and flexibility. It supports both exact and approximate nearest neighbor search, providing a balance between accuracy and speed for various AI and ML applications.
- Ask HN: Who is hiring? (February 2024)
What are some alternatives?
Elasticsearch - Free and Open, Distributed, RESTful Search Engine
Milvus - A cloud-native vector database, storage for next generation AI applications
mu - maildir indexer/searcher + emacs mail client + guile bindings
Weaviate - Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
pagefind - Static low-bandwidth search at scale
faiss - A library for efficient similarity search and clustering of dense vectors.
beir - A Heterogeneous Benchmark for Information Retrieval. Easy to use, evaluate your models across 15+ diverse IR datasets.
pgvector - Open-source vector similarity search for Postgres
ElasticPress - A fast and flexible search and query engine for WordPress.
sonic - 🦔 Fast, lightweight & schema-less search backend. An alternative to Elasticsearch that runs on a few MBs of RAM.
towhee - Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.