Enterprise search

Enterprise search with Apache Solr, Elasticsearch und Co. Let your site visitors find content even faster...

Especially for large websites and portal applications, a high-performance and scalable search function is essential. Many CMS and store systems often already offer an out-of-the-box search function, which usually searches directly in the database (e.g. MySQL, PostgreSQL) for the desired information or relies on regular indexing. However, especially with large databases or complex content structures, this solution quickly reaches its limits.

This can be remedied by a dedicated search solution as a stand-alone application. The most common systems in the enterprise context are Apache Solr and Elasticsearch (ELK-Stack).

Do you need an expert to implement enterprise search?

Niels Langlotz

Tel: +49 176 45 606 488
E-Mail: info(at)typoniels.de

I would like to use my project experience as a developer for your next project, just contact me.

Frequently asked questions & answers

The answer to the following questions may also interest you

The costs for an individual search function are difficult to narrow down across the board and always depend on the complexity and handling or uniformity of the expected database. For very branched content structures, the implementation is more costly than for pages with one or two dominant content types.

In general, the basis of the search function is also crucial, as this may incur software licensing costs. For TYPONiels, I use the software Apache Solr, which is an open source product and therefore free of charge. Costs are only incurred for the set-up, connection to your system and the desired customisations and individualisations. As a rule, you can calculate with 2 to 5 person-days.

Search solutions such as Apache Solr, ElasticSearch and Algolia offer your site visitors a high user experience, especially since they are really fast, deliver more accurate hits compared to database search and come up with features such as typo correction, search suggestions, facets, dynamic rankings and paid results.

But when does it actually make sense to introduce an enterprise search solution, especially since there are corresponding costs for implementation and operation. Good reasons here can be, for example:

  • The website has large amounts of content that overwhelm the user
  • The navigation structure is very convoluted and cannot be mapped in a few levels
  • The website should work a lot with dynamic content and uses lists with filters
  • Several websites are operated, which are to play out content across the board
  • The website has very high access numbers and the database is the bottleneck

An enterprise search solution can also be a real game-changer for the corporate website of a small or medium-sized company:

  • Content can be dynamically displayed in aggregated form after implementation of appropriate templates without additional programming effort.
  • Relevant content / recommendations can be easily implemented
  • Complex multi-level facets can be implemented faster
  • Frequently required functions such as filters, pagination, sorting and a search field with autosuggest (suggestions when typing) are often already implemented and can thus be directly adopted and modified if necessary

There are many different solutions and models for enterprise search systems on the market, which can differ in terms of licensing and use. Some enterprise search solutions are available as open source software, which means they can be downloaded and used for free, but may not offer commercial support options. Other enterprise search solutions are commercially available and offer more extensive functions and support options, but may be more expensive.

In terms of the usage model, there are basically two options: on-premise solutions and cloud-based solutions. On-premise solutions are hosted and managed on the company's own servers, while cloud-based solutions are hosted and managed over the internet. Cloud-based solutions generally offer faster setup and easier management, but may be less flexible than on-premise solutions.

Lucene: Lucene is a free, open-source search library developed by the Apache Foundation. It offers many features such as full-text search, fuzzy matching, and phrase search and has been used as the basis for many other search systems and platforms.

Elasticsearch: Elasticsearch is an open-source search and analysis platform built on the Lucene library. It offers extensive search and analysis functions and is suitable for large amounts of data.

Solr: Solr is also an open-source search platform built on the Lucene library. It is optimized for processing large amounts of data and offers a range of features such as full-text search, faceted navigation, and geographic search.

Angolia: Angolia is a search platform developed by the company Angolia. It offers extensive search functions and is suitable for processing large amounts of data.

SharePoint: SharePoint is a platform from Microsoft that serves as a document management and collaboration system and also provides search functions. SharePoint is particularly popular with companies that already use Microsoft technologies.

Searchperience: Searchperience is a cloud-based search platform developed by the company Searchperience. It offers extensive search functions and integrated analysis tools and is optimized for processing large amounts of data.

FACT-Finder: FACT-Finder is a search platform developed by the company FACT-Finder. It offers extensive search functions and is optimized for processing large amounts of data.

The selection of the right enterprise search solution depends on the requirements and needs of the company. It is important to be clear about the different licensing and usage models when selecting a solution and to choose the solution that is best suited for the company.

The websites of medium-sized and large companies have become much more sophisticated today than they were 15 years ago and generally follow a fairly similarly structured approach in which content is divided into sections, but then output elsewhere (usually prepared) as well.

In development, this approach is usually associated with a high level of programming effort, since the data must first be put into the correct form, as well as all desired functions such as dynamic facets, filters, a pagination or highlighting (Paid Content/ Elevation) must be implemented themselves. For large websites with many content types, this is a lengthy and time-consuming process, which in my opinion can be implemented very well with a powerful search solution such as Apache Solr or Elasticsearch. These systems already come with many useful functions for aggregating and preparing content out of the box and are also much faster than classic database queries (with relations).

Are you curious? Then take a look at my ThinkDigital blog. This blog uses the search solution Apache Solr to display the list view with facets, rubric pages and the relevant posts on the detail page.

I would be happy to advise you on the possible uses of an enterprise search solution such as Apache Solr for flexible aggregation of customized content.