Leading Analytical Engines for Enterprise Search

Enterprise search is a completely different ball game from the internet search. As the plethora of content been produced every day across the enterprise, it has burst forth as one of the most challenging areas in business today.

CIO Review

Enterprise search is a completely different ball game from the internet search. As the plethora of content been produced every day across the enterprise, it has burst forth as one of the most challenging areas in business today. Employees expect to locate relevant data with as conveniently as they could navigate on Google and other prominent web search engines. However, the kind of search options that enterprises look for in the search engines to obtain better results is much deeper in terms of its demands.

Today, the increasingly adoption of cloud servers aiding enterprises to avail the search features via cloud platform for quick response time. It not only provides readily available data but also supports scalability by reducing infrastructural and maintenance costs. There are a number of providers in this space offering “search in the cloud” services freeing them from dealing with search software.

Below is the snapshot of the companies that are prominent in the Enterprise search landscape:

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Google Search Appliance (GSA)

GSA—Google’s first business focused product—was introduced in 2002 became popular in corporations. The magic mystery of Google search site had already taken over the people’s mind, all which made it a clear choice for intranet search and public-facing web content.

Unfortunately, Google announced the "end of life" for all its GSA in February this year. However, the internet giant will continue to providing security updates, bug fixing, and give full technical support for the next three years. To achieve effective and improved results for enterprise search, the tech giant will begin cloud-based search solution. Google predicts cloud search to be assistive and powered by innovations in machine learning, natural language capabilities, and graph search.

Microsoft SharePoint

With time, SharePoint has become the top drawer for team collaboration and content management. Yet, it is difficult to overlook the fact that SharePoint is sometimes difficult to support and expensive to license. Also, for searching purpose, this decent search platform in itself may not be the classified fit for heavy duty search applications.

SharePoint Server 2016 promises better user productivity and foundation for future with today’s rapidly changing business and technology environment.

Check Out: Top Enterprise Startups in APAC

Coveo

Holding to its distinctiveness in the market, Coveo enables users to conduct powerful enterprise-wide searches leveraging intelligent search solutions and predictive analytics. Coveo connects people from a large number of enterprise repositories and is broadly applicable in areas such as forensics, supply chain management, and the medical sector. Sometimes, difficulties are created in terms of indexing and easing retrieval of all the data residing inside cloud repositories.

“Think of a world in which every document an executive needs on any platform is instantly organized, indexed and searchable just as consumers search the Web. This type of environment is where the cloud’s hidden knowledge can be extracted, and correlated to enterprise content,” Louis Tetu, CEO of Coveo, told to Forbes in an Interview with Bruce Rogers.

Attivio

Born out of deep experience in business intelligence and enterprise search, the idea for Attivio technology revolves around linking the entity from structured world of business intelligence data to the unstructured world. It demands the usage of a variety of techniques such as key phrase extraction and sentiment analysis to gain business insights from unstructured data.

Recently, Attivio has positioned its product "active intelligence engine" technology as a Data Unification product. It would be interesting to see how Attivio can enhance other cloud applications to relate data across the architecture, as it grows.

Solr or Elasticsearch – New Promise or Good Old…?

If a few million documents are infused into the index for new content, Solr might come under pressure while Elasticsearch brings the ability of completing the task without a hitch. Elasticsearch takes the stage when it is about distributed search but Solr is complete, reliable, and fast.

Solr search server—a spin-off from Lucene—offers massive failover and redundancy with its Solr Cloud. However, Elasticsearch offers the perfect architecture for real-time search as it has a default refresh interval already set to one second.

Lucidworks

Lucidworks markets a commercial search platform called Fusion and employs a large number of the Lucene/Solr committers. Lucidworks has just tapped into the IBM Watson Developer Cloud platform for its Fusion platform that assists developers in creating enterprise search applications. It offers a spectrum of features for tweaking, tuning, and developing discovery applications. This facilitates companies to understand their data and act on insights.

The startup came into existence in 2007 and search extremely large content repositories providing flexibility to maximize user capabilities.

So, which search platform should one choose?

It depends. Companies need to do thorough research on the basis of following requirements:

• Types and formats of the documents one need to search

• Check how secured the documents are

• Size, Format and the number of documents

• Location, where does the content live? SharePoint? File systems? DBMS? Or anywhere else

• Who are the clients, Library scientists or average web visitors? And, are they skilled enough?

Analyse the reporting capability as well.

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