Apache Lucene VS Apache Solr

MongoDB Atlas Search is an extension to the built-in indexing capabilities that are part of MongoDB itself, using the awesome open source indexing and query library Lucene. MongoDB has built a wrapper around Lucene called mongot. Mongot has two responsibilities: First, it follows the change stream of any collection you choose to index and builds Lucene indexes asynchronously. Second, when you run the $search aggregation stage in a MongoDB query, mongot will be invoked to perform a Lucene query on the index and return a stream of document ids for further processing and data retrieval.

Implementing full-text search in an application can be challenging, but Hibernate Search simplifies the process by offering a built-in solution that requires minimal configuration. It seamlessly integrates with powerful search engines like Elasticsearch and Lucene, enabling efficient and scalable search capabilities.

In today’s digital landscape, open source projects are the engines of innovation that drive technological progress and collaboration. One such powerhouse is Apache Lucene. Recognized as one of the most advanced high-performance text search engine libraries, Apache Lucene not only excels technically but also sets a benchmark in open source business models and sustainable funding. In this post, we delve into Lucene’s unique ecosystem, its transparent licensing under the Apache License 2.0, and the robust community that fuels its continuous advancements. For a deeper dive into these topics, check out the original article “What is Apache Lucene? The Open Source Business Model, Funding, and Community.”

It just be this easy with a little Java elbow grease. And because it’s fairly straightforward to send data into Lucene and then query it powerfully, and because Mr. Cutting nurtured such a benevolent, inviting yet demanding, open source environment, an entire ecosystem of add-ons, forks, ports, wrappers, and companies, and ... And ... AND!

Solr is based on the Lucene library, as is Elastic. I mention this because these two search engines provide most private web site search capabilities on the internet. I started using Lucene around 25 years ago in Perl - it works well.

There are already many project about search:

- https://www.marginalia.nu/

- https://searchmysite.net/

- https://lucene.apache.org/

- elastic search

- https://presearch.com/

- https://stract.com/

- https://wiby.me/

I think that all project are fun. I would like to see one succeeding at reaching mainstream level of attention.

I have also been gathering links meta data for some time. Maybe I will use them to feed any eventual self hosted search engine, or language model, if I decide to experiment with that.

- domains for seed https://github.com/rumca-js/Internet-Places-Database

- bookmarks seed https://github.com/rumca-js/RSS-Link-Database

- links for year https://github.com/rumca-js/RSS-Link-Database-2024

Elasticsearch is based on Lucene and is used by various companies and developers across the world to build custom search solutions.

elastic search is kinda heavyweight infra for a small project. Its built on top of apache lucene (https://lucene.apache.org), which you can use directly.

Elasticsearch is based on Lucene, which is built in Java. This means that monitoring the Java Virtual Machine (JVM) memory is crucial to understand the current usage of the whole system.