Typesense
Apache Solr
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Typesense | Apache Solr | |
---|---|---|
129 | 31 | |
17,876 | 4,365 | |
4.4% | 0.0% | |
9.8 | 0.0 | |
6 days ago | 2 months ago | |
C++ | Java | |
GNU General Public License v3.0 only | 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.
Typesense
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Website Search Hurts My Feelings
There are actually plenty of non-ES products that are way easier to integrate and tune (and get better results with less effort).
- Typesense (https://github.com/typesense/typesense)
- Algolia
- Google Programmable Search Engine (https://programmablesearchengine.google.com/about/)
- Remote Machine Learning and Searching on a Raspberry Pi 5
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Open Source alternatives to tools you Pay for
Typesense - Open Source Alternative to Algolia
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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.
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Vector databases: analyzing the trade-offs
I work on Typesense [1] (historically considered an open source alternative to Algolia).
We then launched vector search in Jan 2023, and just last week we launched the ability to generate embeddings from within Typesense.
You'd just need to send JSON data, and Typesense can generate embeddings for your data using OpenAI, PaLM API, or built-in models like S-BERT, E-5, etc (running on a GPU if you prefer) [2]
You can then do a hybrid (keyword + semantic) search by just sending the search keywords to Typesense, and Typesense will automatically generate embeddings for you internally and return a ranked list of keyword results weaved with semantic results (using Rank Fusion).
You can also combine filtering, faceting, typo tolerance, etc - the things Typesense already had.
[1] https://github.com/typesense/typesense
[2] https://typesense.org/docs/0.25.0/api/vector-search.html
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Creating an advanced search engine with PostgreSQL
For something small with a minimal footprint, I'd recommend Typesense. https://github.com/typesense/typesense
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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.
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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.
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[Guide] A Tour Through the Python Framework Galaxy: Discovering the Stars
Try tigris | typesense for faster search
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Is it worth using Postgres' builtin full-text search or should I go straight to Elastic?
I’m also checking out Typesense as a possibility for replacing Elastic: https://typesense.org/
Apache Solr
- Iniciando no Elasticsearch: Conceitos básicos
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YaCy, a distributed Web Search Engine, based on a peer-to-peer network
There are already many project about search:
- https://www.marginalia.nu/
- https://searchmysite.net/
- https://lucene.apache.org/
- elastic search
- https://presearch.com/
- https://stract.com/
- https://wiby.me/
I think that all project are fun. I would like to see one succeeding at reaching mainstream level of attention.
I have also been gathering links meta data for some time. Maybe I will use them to feed any eventual self hosted search engine, or language model, if I decide to experiment with that.
- domains for seed https://github.com/rumca-js/Internet-Places-Database
- bookmarks seed https://github.com/rumca-js/RSS-Link-Database
- links for year https://github.com/rumca-js/RSS-Link-Database-2024
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Getting started with Elasticsearch + Python
Elasticsearch is based on Lucene and is used by various companies and developers across the world to build custom search solutions.
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Tools to use to query and index data?
elastic search is kinda heavyweight infra for a small project. Its built on top of apache lucene (https://lucene.apache.org), which you can use directly.
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Top metrics for Elasticsearch monitoring with Prometheus
Elasticsearch is based on Lucene, which is built in Java. This means that monitoring the Java Virtual Machine (JVM) memory is crucial to understand the current usage of the whole system.
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Cross data type search that wasn’t supported well using Elasticsearch
Apache Lucene which seems to have a lot more features than Elasticsearch
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How to find closest keyphrase match in text?
Generally with term vectors and a tf-idf index. Lucene is a good starting place to help.
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Java Library to perform string search
try elasticsearch or solr, behind the scenes they both use https://lucene.apache.org/ if you don't want basically a full nosql database service, but I'd just slap solr up and call it a day.
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Top 8 Open-Source Observability & Testing Tools
OpenSearch is an open-source database to ingest, search, visualize, and analyze data. It’s built on top of Apache Lucerce, a FOSS library for indexing and search, which OpenSearch leverages for more advanced analytics capabilities, like anomaly detection, machine learning, full-text search, and more.
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grep like search with preprocessing
Lucene is the thing you think you need. Elastic Search is a nice wrapper for it. But these are Java, so maybe you want Sphinx Search (C++) or MeiliSearch (Rust).
What are some alternatives?
MeiliSearch - A lightning-fast search API that fits effortlessly into your apps, websites, and workflow
OpenSearch - 🔎 Open source distributed and RESTful search engine.
Elasticsearch - Free and Open, Distributed, RESTful Search Engine
meilisearch-laravel-scout - MeiliSearch integration for Laravel Scout
loki - Like Prometheus, but for logs.
sonic - 🦔 Fast, lightweight & schema-less search backend. An alternative to Elasticsearch that runs on a few MBs of RAM.
Apache Lucene - Apache Lucene.NET
vespa - AI + Data, online. https://vespa.ai
ClickHouse - ClickHouse® is a free analytics DBMS for big data