From official definitions:
- Solr is highly reliable, scalable and fault tolerant, providing distributed indexing, replication and load-balanced querying, automated failover and recovery, centralized configuration and more. Solr powers the search and navigation features of many of the world's largest internet sites.
- Elasticsearch is a distributed, RESTful search and analytics engine capable of addressing a growing number of use cases. As the heart of the Elastic Stack, it centrally stores your data for lightning fast search, fineβtuned relevancy, and powerful analytics that scale with ease.
- MeiliSearch is a powerful, fast, open-source, easy to use and deploy search engine. Both searching and indexing are highly customizable. Features such as typo-tolerance, filters, and synonyms are provided out-of-the-box.
The question is, between the three, which one is best suitable for search operations which can be embended into a website and other applications? Answering this question requires clear and extensive understanding of how both platform operate. Let's take a look into both:
- 01-solr-techproducts.ipynb π Techproducts demo from solr quickstart tutorial
- 02-solr-films.ipynb π Films demo from solr quickstart tutorial
- 03-schema-api.ipyn π Solr schema definition using REST API
- 04-indexing-custom-docs.ipynb π Elaborate guide of how to index custom documents. Composed using details adapted from Solr Reference Guide
- 05-search-api.ipynb π A continuation of
04-indexing-custom-docs.ipynb
with focus on search operations - 06-sophisticated-indexing-and-search.ipynb π Fine tune query results using Solr
analyzers
,tokenizers
andfilters
.