MeiliSearch
quickwit
Our great sponsors
MeiliSearch | quickwit | |
---|---|---|
129 | 64 | |
42,538 | 5,653 | |
2.5% | 6.6% | |
9.8 | 9.8 | |
4 days ago | 6 days ago | |
Rust | Rust | |
MIT License | GNU General Public License v3.0 or later |
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.
MeiliSearch
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Publish/Subscribe with Sidekiq
We needed to introduce a new service for search. As we settled on using meilisearch, we needed a way to sync updates on our models with the records in meilisearch. We could've continued to use callbacks but we needed something better.
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The Mechanics of Silicon Valley Pump and Dump Schemes
Meilisearch
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What is Hybrid Search?
In this case, a good strategy is to use vector search only when the keyword/prefix search returns none or just a small number of results. A good candidate for this is MeiliSearch. It uses custom ranking rules to provide results as fast as the user can type.
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Create a ChatBot with VertexAI and LibreChat
With the VertexAI endpoint set up and tested, our next step is to work with LibreChat. LibreChat is an open-source ChatGPT clone that can integrate with various AI models, including the PaLM 2 models via the VertexAI API. It's built using React, MongoDB, and Meilisearch technologies.
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Pg_bm25: Elastic-Quality Full Text Search Inside Postgres
Meilisearch seems like it is the best open source option.
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Vector storage is coming to Meilisearch to empower search through AI
Starting with v1.3, you can use Meilisearch as a vector store. Meilisearch allows you to store vector embeddings alongside your documents conveniently. You will need to create the vector embeddings using your third-party tool of choice (Hugging Face, OpenAI). As we published the first v1.3 release candidate, you can try out vector search today.
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[N] Open-source search engine Meilisearch launches vector search
I work at Meilisearch, an open-source search engine built in Rust. 🦀
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Creating search engine for your local network - Is it even possible?
https://www.meilisearch.com/ https://github.com/meilisearch
- Meilisearch across the Semantic Verse
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Docker file to allow serving/hosting of a directory of files via web browser
1) your program uses a db to index but the actual search is querying too much data at a time and you need to chop the server side query into smaller/faster queries. you could build your own efficient search with something like https://github.com/meilisearch/meilisearch
quickwit
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Show HN: Quickwit – OSS Alternative to Elasticsearch, Splunk, Datadog
Hi folks, Quickwit cofounder here.
We started Quickwit 3 years ago with a POC, "Searching the web for under $1000/month" (see HN discussions [0]), with the goal of making a robust OSS alternative to Elasticsearch / Splunk / Datadog.
We have reached a significant milestone with our latest release (0.7) [1], as we have witnessed users of the nightly version of Quickwit deploy clusters with hundreds of nodes, ingest hundreds of terabytes of data daily, and enjoy considerable cost savings.
To give you a concrete example, one company is ingesting hundreds of terabytes of logs daily and migrating from Elasticsearch to Quickwit. They divided their compute costs by 5x and storage costs by 2x while increasing retention from 3 to 30 days. They also increased their durability, accuracy with exactly-once semantics thanks to the native Kafka support, and elasticity.
The 0.7 release also brings better integrations with the Observability ecosystem: improvements of the Elasticsearch-compatible API and better support of OpenTelemetry standards, Grafana, and Jaeger.
Of course, we still have a lot of work to be a fully-fledged observability engine, and we would love to get some feedback or suggestions.
To give you a glance at our 2024 roadmap, we planned to focus on Kibana/OpenDashboard integration, metrics support, and pipe-based query language.
[0] Searching the web for under $1000/month: https://news.ycombinator.com/item?id=27074481
[1] Release blog post: https://quickwit.io/blog/quickwit-0.7
[2] Open Source Repo: https://github.com/quickwit-oss/quickwit
[3] Home Page: https://quickwit.io
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S3 Express Is All You Need
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 have a lot of requests.
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Show HN: Quickwit – Cost-Efficient OSS Search Engine for Observability
Hi HN, I’m one of the builders of Quickwit, a cloud-native OSS search engine for observability. As of 2023, we support logs and traces, metrics will come in 2024.
You know the pitch: while software like Datadog or Splunk are great, they often comes with hefty price tags. Our mission is to offer an affordable alternative. So we’ve built Quickwit, we’ve made it compatible with the observabilty ecosystem (OpenTelemetry, Jaeger, Grafana) and above all, we’ve made it cost-efficient / “easy” to scale (well it’s never easy to scale to petabytes..).
To give you a glance at the engine performance I made a benchmark on the GitHub Archive dataset, 23 TB of events, here are the main observations:
Indexing: costs $2 per ingested TB. With 4CPU, throughput is at 20MBs However, you'll observe > 30MB throughput on simpler datasets, like logs and traces.
Search: a typical query costs $0.0002 per TB (considering both CPU time and GET request costs). Using 8CPU, a simple query on 23TB is achieved in under a second.
Storage: on S3, it costs $8 per ingested TB per month on the GitHub Archive dataset. With logs and traces, you might see costs around $5/ingested TB due to a 2x better compression ratio.
I'm eager to get your thoughts on this!
Benchmark: https://quickwit.io/blog/benchmarking-quickwit-engine-on-an-...
Github repo: https://github.com/quickwit-oss/quickwit/
Website: https://quickwit.io/
- On S3, it costs $8 per ingested TB per month on the GitHub Archive dataset. With logs and traces, you might see costs around $4/ingested TB due to a 2x better compression ratio.
I'm eager to get your thoughts on this!
[0] Benchmark: https://quickwit.io/blog/benchmarking-quickwit-engine-on-an-...
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Ask HN: Who is hiring? (September 2023)
Quickwit (https://quickwit.io/) | Paris, France | Onsite and remote (based in Europe) | Full-time
The company is fully remote but we also have a small office in Paris. We prefer candidates based in Europe but can make exceptions for the right profiles.
- Senior Software Engineer 80-110k€ + 0.25-1% equity based on experience.
We’re looking for a senior software engineer to contribute to [Quickwit](https://github.com/quickwit-oss/quickwit), our open-source search and analytics engine. We have an ambitious roadmap for the next 18 months (performance optimization, distributed storage, support for SQL, query optimizer, revamp of our execution engine, etc.), and this is a great opportunity to shape the future of Quickwit while tackling fun and challenging problems in the field of distributed databases.
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Quickwit 0.6.0 - Search and analytics on billions of logs with minimal hardware
Link: https://github.com/quickwit-oss/quickwit
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Show HN: Quickwit – Cost-efficient Elasticsearch alternative on object storage
- Another nice comment seen on HN « it seems to be very easy to run, not very IO intensive, and running fine on a single node with modest hardware with >2 billion log rows. It has a really cool dynamic schema feature too.» [9]
Fun fact: at least 4 users are using Garage[10] as the object storage, this OSS project looks really promising and made the HN front page a few months ago[11], we really cherish the OSS for this kind of unexpected combination.
Any feedback positive/negative always greatly appreciated here!
[0] Quickwit repo: https://github.com/quickwit-oss/quickwit
[1] Searching the web under 1000$/month: https://news.ycombinator.com/item?id=27074481
[2] Chitchat gossip library: https://github.com/quickwit-oss/chitchat
[3] Columnar format: https://github.com/quickwit-oss/tantivy/tree/main/columnar
[4] Tantivy library: https://github.com/quickwit-oss/tantivy/
[5] Whichlang library: https://github.com/quickwit-oss/whichlang
[6] GitHub Archive demo in terminal: https://www.youtube.com/watch?v=SNq3bARRlDI
[7] Indexing performance: https://twitter.com/fulmicoton/status/1638016949459488768
[8] https://twitter.com/arnonrgo/status/1645429632303235073?s=20
[9] https://news.ycombinator.com/item?id=35742544
[10] Garage object storage: https://garagehq.deuxfleurs.fr/
[11] https://news.ycombinator.com/item?id=33853539
What are some alternatives?
Typesense - Open Source alternative to Algolia + Pinecone and an Easier-to-Use alternative to ElasticSearch ⚡ 🔍 ✨ Fast, typo tolerant, in-memory fuzzy Search Engine for building delightful search experiences
zincsearch - ZincSearch . A lightweight alternative to elasticsearch that requires minimal resources, written in Go.
Elasticsearch - Free and Open, Distributed, RESTful Search Engine
Searx - Privacy-respecting metasearch engine
sonic - 🦔 Fast, lightweight & schema-less search backend. An alternative to Elasticsearch that runs on a few MBs of RAM.
rust-postgres - Native PostgreSQL driver for the Rust programming language
OpenSearch - 🔎 Open source distributed and RESTful search engine.
Yacy - Distributed Peer-to-Peer Web Search Engine and Intranet Search Appliance
RedisLess - RedisLess is a fast, lightweight, embedded and scalable in-memory Key/Value store library compatible with the Redis API.
Apache Solr - Apache Lucene and Solr open-source search software
redis-rs - Redis library for rust
loki - Like Prometheus, but for logs.