Elasticsearch VS Whoosh

Compare Elasticsearch vs Whoosh and see what are their differences.

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Elasticsearch Whoosh
91 -
67,531 -
1.1% -
10.0 -
5 days ago about 8 years ago
Java
GNU General Public License v3.0 or later -
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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

Posts with mentions or reviews of Elasticsearch. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-10-18.

Whoosh

Posts with mentions or reviews of Whoosh. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning Whoosh yet.
Tracking mentions began in Dec 2020.

What are some alternatives?

When comparing Elasticsearch and Whoosh you can also consider the following projects:

OpenSearch - 🔎 Open source distributed and RESTful search engine.

django-haystack - Modular search for Django

Apache Superset - Apache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset]

elasticsearch-dsl-py - High level Python client for Elasticsearch

bleve - A modern text/numeric/geo-spatial/vector indexing library for go

pysolr - Pysolr — Python Solr client

pgvector - Open-source vector similarity search for Postgres

solrpy - Automatically exported from code.google.com/p/solrpy

MeiliSearch - A lightning-fast search API that fits effortlessly into your apps, websites, and workflow

esengine - ElasticSearch ODM (Object Document Mapper) for Python - pip install esengine

Search Engine Parser - Lightweight package to query popular search engines and scrape for result titles, links and descriptions