elasticsearch-py
Typesense
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elasticsearch-py | Typesense | |
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21 | 129 | |
4,136 | 17,876 | |
0.8% | 4.4% | |
8.7 | 9.8 | |
6 days ago | 5 days ago | |
Python | C++ | |
Apache License 2.0 | GNU General Public License v3.0 only |
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.
elasticsearch-py
- Verify Connection to Elasticsearch (2021)
- An alternative to Elasticsearch that runs on a few MBs of RAM
- Help With Psort.py -> ELK
- Elastic Open Sources Their Endpoint Security Protection YARA Ruleset
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OpenSearch – open-source search and analytics based on Apache 2.0 Elasticsearch
FD: I have a friend who works at Elastic, though he doesn't really colour my opinions of things.
> Firstly, dick moves like this: https://github.com/elastic/elasticsearch-py/pull/1623
I understand that this is unpopular, but you can make a very strong argument that it's to prevent weird errors in the future. I'm also guilty of littering my code with Asserts to ensure the universe is working fine.
The alternative is to allow it to work and then you end up with weird issues like when you connect mysql client to mariadb server (and vice-versa): https://stackoverflow.com/questions/50169576/mysql-8-0-11-er...
> Secondly, I don't buy the argument from Elastic any more. Yes, the ethical thing to do when you're making money from someone's work is at least contribute back. At the same time though, they're making money from packaging it up and selling it _as a service_. That "as a service" part is where they're making the bucks.
That's just an opinion, yes they have a service, and yes it competes with Amazon. Is it cool for Amazon to take a body of work and sell it without supporting it? Are amazon actually supporting it? Is it the same as Elastic using Lucene? (not really because Elastic submits a the majority of fixes to Lucene, but, you get it).
it's kinda gray, I'm sure Amazon thinks they're the good guy, but it's hard for me to look at Elastic as the bad guy in all this.
- Struggling reading code with type hints
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I Don't Think Elasticsearch Is a Good Logging System
Oh man, https://github.com/elastic/elasticsearch-py/issues/1734 is a disappointing read. I know ES wants to save their business, but alienating users isn't exactly the path to success.
- Elasticsearch adding code to reject connections to OpenSearch clusters or to clusters running open source distributions of ES7
- Official Elasticsearch Python library no longer works with open-source forks
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/
What are some alternatives?
searxng - SearXNG is a free internet metasearch engine which aggregates results from various search services and databases. Users are neither tracked nor profiled.
MeiliSearch - A lightning-fast search API that fits effortlessly into your apps, websites, and workflow
quickwit - Cloud-native search engine for observability. An open-source alternative to Datadog, Elasticsearch, Loki, and Tempo.
Elasticsearch - Free and Open, Distributed, RESTful Search Engine
helm-charts
Apache Solr - Apache Lucene and Solr open-source search software
orama - 🌌 Fast, dependency-free, full-text and vector search engine with typo tolerance, filters, facets, stemming, and more. Works with any JavaScript runtime, browser, server, service!
meilisearch-laravel-scout - MeiliSearch integration for Laravel Scout
qryn - qryn is a polyglot, high-performance observability framework for ClickHouse. Ingest, store and analyze logs, metrics and telemetry traces from any agent supporting Loki, Prometheus, OTLP, Tempo, Elastic, InfluxDB and many more formats and query transparently using Grafana or any other compatible client.
loki - Like Prometheus, but for logs.
evtx2es - A library for fast parse & import of Windows Eventlogs into Elasticsearch.
sonic - 🦔 Fast, lightweight & schema-less search backend. An alternative to Elasticsearch that runs on a few MBs of RAM.