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, fine‑tuned 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 👉 Techproducts demo from solr quickstart tutorial
• 02-solr-films.ipynb 👉 Films demo from solr quickstart tutorial
• 03-schema-api.ipyn 👉 Solr schema definition using REST API
• 04-indexing-custom-docs.ipynb 👉 Elaborate guide of how to index custom documents. Composed using details adapted from Solr Reference Guide
• 05-search-api.ipynb 👉 A continuation of 04-indexing-custom-docs.ipynb with focus on search operations
• 06-sophisticated-indexing-and-search.ipynb 👉 Fine tune query results using Solr analyzers, tokenizers and filters.