What is the difference between Apache Lucene and Apache Solr? Should you be using Lucene or Solr? If you are asking these questions, you are most probably trying to build a search engine right now. A search engine is an effective solution for finding the right data and information needed from various sources, and it can help a lot in an information system of a company or any enterprise-grade institution handling large amounts of data daily.
Both Lucene and Solr are the most popular options that people usually use to build a search engine. However, choosing between Lucene and Solr can be confusing for someone who is not familiar with the two. Of course, a simple way to describe the comparison between the two is that of a car and an engine. Solr is like a car; you can drive it right away without having to build everything from scratch. On the other hand, Lucene is an engine; with an engine, you can build and customize everything from zero to build the ultimate vehicle. Below, we will see the more detailed differences between Lucene and Solr.
Lucene is a free, open-source information retrieval software library that is written completely in Java. However, today, it has been ported to other programming languages, such as C#, C++, Object Pascal, Python, Ruby, Perl, and PHP. It was released for the first time in 1999 by Doug Cutting and is now supported by Apache Software Foundation. Lucene has been widely praised for the powerful full text indexing and searching capabilities, and it has been implemented in various Internet search engines as well as local search engines.
On the other hand, Solr, pronounced “solar”, is an open-source search platform built on top of Lucene. It is also written in Java, and it has the Lucene Java search library at its core. Even so, Solr works as a standalone full-text search server. Solr has various added features and capabilities, including hit highlighting, real-time indexing, faceted search, dynamic clustering, as well as NoSQL features and rich document handling. The scalability and fault tolerance are exceptional, and the APIs have made Solr usable in most popular programming languages and applications without requiring Java coding. Solr was originally created by Yonik Seeley in 2004 at CNET Networks, but was donated to Apache Software Foundation in 2006. In 2010, Lucene and Solr projects were merged by the developers.
Lucene vs. Solr: Do You Need a Car or an Engine?
The very first question that you need to consider when choosing between Lucene and Solr is whether you want to build something from zero or start with a ready-to-use solution that is also customizable.
If you prefer to use something that is ready-to-use right away, Solr is the answer. The fact is, it is the answer for most people, as it is a stand-alone search server that allows you to build a running search server without any programming. Solr is the answer for people with little to no programming background, as well as programmers who don’t have the time or resources to build from scratch. Just by editing and configuring an XML file, it will be ready to be implemented onto your company’s website within minutes. It provides you an HTTP API that exposes a lot of Lucene’s functionality, a nice monitoring/debugging interface, and pre-set parameters with good default values.
On the other hand, Lucene is a powerful search engine framework that enables us to add search capability to our application while hiding the complex search-related operations behind. Not just Solr, but any application can actually use this library. However, it gives you a Java API, and you will need some serious Java programming in order to construct a full-text search engine from it. Hence, it will require a lot more time, effort, skill, and resources. However, the result can be much more customizable. Lucene can be a great choice if you need low-level access to Lucene’s API classes (using Solr may be more of a hindrance than a help due to being an extra layer of indirection), or if you want to use a different application other than Solr on top of Lucene, such as ElasticSearch.
Lucene vs. Solr: Features
Solr is built around Lucene, but it is not just an HTTP-wrapper. Solr is known to add more arsenals to Lucene. The added functionalities and features include:
– HTTP/XML and JSON APIs,
– Faceted search and filtering,
– Geospatial search,
– Hit highlighting,
– Fast incremental updates & index replication,
– Web administration interface.
In addition, it is important to point out that Solr is also very flexible. It has various pluggable API points that allow you to throw in your code. There are many people who can use Lucene but prefer to use Solr because it is easier to use while still being customizable to a fairly high degree.
Lucene vs. Solr: Why and When to use
Below is the general rule to help you decide whether to use Lucene or Solr.
Lucene is the way to go if:
– You are a search engineer,
– You are a programmer,
– Your requirements demand all sorts of low-level customization to Lucene,
– You want to have full control over the internals of Lucene,
– You are willing to take care of the infrastructure elements, such as distribution and scaling.
Solr is the way to go if:
– At least one of the points above is invalid in your current condition,
– Your infrastructure requirements outweigh the search customization requirements,
– You want to use something that is ready-to-use, even without Java knowledge.
|- Free, open-source information retrieval software library||- An open-source search platform built on top of Lucene|
|- Written completely in Java, but has been ported to some other languages||- Written in Java, but has HTTP/XML and JSON APIs|
|- Requires programming||- Doesn’t require programming|
|- Will require more time, effort, skill, and resources to use||- Much simpler and easier to use, ready-to-use almost right away|
|- Can be more flexible and customizable, can be used as the core for another application besides Solr||- Highly flexible and customizable|
In general, Solr is almost always the best solution for a search engine application. It will be much simpler and easier to use. It is also very flexible and still customizable. It even adds various features and functions on top of Lucene. However, if you really need to perform low-level customizations to Lucene, and you can take care of the infrastructure elements such as distribution and handling, then there you go.