Searches are a very crucial part of any application. Performing multiple searches on terabytes and petabytes of data can be challenging when speed, performance, and high availability are core requirements. This is where an Open-Source Search engines steps in. They are software programs whose code is visible to all & they are built to perform lightning-fast searches by matching the keywords typed in by the user to the items in the Database & displaying the results to the user.
Here are all of the most popular Open-Source Search Engines available:
Typesense
Typesense is the most popular search engine available in the market & is being adopted by many of the top companies. The reasons are many, however, its open-source nature with typo-tolerance tops the charts. The search engine has been optimized for instant sub 50ms searches while maintaining an intuitive developer experience.
How is Typesense different?
Typo-Tolerance: Spelling errors are now a thing of the past. With Typesense's typo tolerance, it can automatically correct the typos you make.
Dynamic Sorting: Sort all records easily using any of the fields in your document. For Eg: sort by Category, sort by price, and so on. All of this while not needing duplicate indices!
Filtering & Faceting: Only search for records that match a filter that you provide. Search for aggregate field values and get counts, minimum, maximum, & average of values across all records so that you can drill down & refine your results.
Tunable Ranking: It is effortless to customize your results to perfection using Typesense via flexible and fast query-time sorting.
Grouping & Distinct: Typesenses groups similar results to provide variety in your search results. For example, you can combine all colour variations of a single shirt into a single result.
Easy Version Upgrades: Upgrading to Typesense recent upgrades are as simple as pushing binaries and restarting Typesense, & voila, you are now running the latest version of the blazing-fast Typesense.
Federated Search: Search across multiple collections or what is also called indices, all in a single HTTP request. For example, you can search for both products and brands, all in a single search query.
No Runtime Dependencies: Users can run Typesense on local machines with just one command. It is that simple!
Geo-Search: You can also Search & sort results within a certain distance from a latitude/longitude or within a polygon region! How cool is that?
Multi-tenant API Keys: Store multiple users' data in a single index, & you can create API keys for each user that restrict access to just their data, to create a simple access system using just API Keys.
Synonym Support: Define words as equivalents of each other, so searching for a particular word will also return results for the synonyms defined by you.
API Library & Plugin Architecture: Typesense supports many other API Libraries & Plugins written in languages such as Javascript, Golang, Php, Ruby, Python, Dart & more. If you don't find a library, you can reach out to them to collab on one too!
Thorough Documentation: The Typesense Documentation is one of the best amongst search engines because it also provides you with live demos of where Typesense is doing & can do wonders! E-commerce storefront with Next.js, Typesense live demo with 3k products, instantly search 32 million songs, 28 million books & so much more!
To know more about the open-source project, guide to contribute and be a part of active dev groups, join Typesense's Slack community today.
Indri Lemur
Indri search engine is a component of the Lemur Project, a collaboration between the Center for Intelligent Information Retrieval at the University of Massachusetts Amherst and the Language Technologies Institute at Carnegie Mellon University. It is an open-source search engine and the query language used in Indri allows researchers to index data or structure documents using simple command-line instructions.
Key Features:
Support Complex Queries: Indri Lemur supports complex queries involving evidence combination and the ability to specify a wide variety of constraints involving proximity, syntax, extracted entities, and document structure.
Effectiveness: The retrieval model offers superior effectiveness across a range of query and document types; For example: Web, cross-lingual, ad-hoc2.
Query Language and Retrieval Model: The query language and retrieval model of the Indri Lemur search engine supports the retrieval at different levels of granularity (For example: sentence, passage, XML field, document, multi-document).
System Architecture: The system architecture supports very large databases, multiple databases, optimized query execution, fast indexing, concurrent indexing and querying, and portability.
Apache Solr
Apache Solr is yet another open-source search engine that is popular, and built on top of Apache Lucene. Let's deep dive & see what features does it offer:
Scalable and Fault-Tolerant: This feature is built on the Apache Zookeeper, Solr makes it easy to scale up and down. Solr offers replication, distribution, rebalancing, & fault tolerance out of the box, which isn't quite up to the mark as Typesense but is still used often.
Near Real-Time Indexing: Solr uses Lucene's Near Real-Time Indexing ability to make sure you see your content in real-time, a feature already present in Typesense, as mentioned above. Typesense was built from scratch, unlike Solr that was built on top of Lucene.
Plugin Architecture: While Solr does publish many extension points that make it easy to add plugins, it isn't as vast & extensive as Typesense. Because Typesense provides support for almost all Languages & Tech Stacks & are continuously adding more.
High-Traffic: Solr claims to have been optimized for high volume traffic, a feature already included in Typesense. They beat high volume traffic with better result times, becoming the best option for High Volume Traffic.
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