MongoDB Atlas Search
Before MongoDB Atlas Search, developers had to rely on various other solutions to implement search functionality in their applications. Some of these solutions included:
- Algolia: This is a powerful and flexible search and discovery solution. Even though it's used in many applications, it can be quite costly. This cost is driven by the quantity of records stored and the volume of API actions performed. If you have a large dataset, Algolia might not be the best fit for you.
- Elasticsearch: This is a distributed, RESTful search and analytics engine suitable for a growing number of use cases. Just like Atlas Search, it is based on Apache Lucene.
- Solr: This is another powerful search platform built on Apache Lucene. It's highly reliable, scalable, and fault-tolerant, providing distributed indexing, replication, and load-balanced querying.
- The built-in $text index of MongoDB: This is the easiest solution to implement but was not suitable...
