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Exploring Enterprise Search Solutions

Enterprise Search is an all encompassing term that includes both Enterprise Search Software and Enterprise Search Engines. The industry is murky about the terms and there is not consistent differentiation for buyers to understand what will work best for their organization. Gartner has a few different classifications like Insight Engines or their Enterprise Search Magic Quadrant while G2 has both Software and Engines jointly listed in their Best Enterprise Search Solutions list. Regardless of aggregation type or vendor review classification, it is important to establish a clear difference between Software and Engines to leverage the appropriate solution effectively. 


Enterprise Search Software

Enterprise Search Software is a managed service that empowers businesses to index, search, and deliver search results to users from internal sources. The service provider manages the infrastructure, the technology, and ensures your organization sees the greatest value in implementing an enterprise search solution. Best of all, your employees and customers receive the benefits of Enterprise Search without the cost and headache of managing the infrastructure. Enterprise Search Software integrates with existing internal systems and databases, indexes the data, and delivers search results within the flow of work that can lead to actionable insights.

Leveraging a service provider can help your organization deliver more impact with fewer resources. But leveraging Enterprise Search Software does have considerations. First and foremost the solution must exist within your organization's technology ecosystem. The search software must integrate with your data sources and document cloud storage providers like Google Drive, Microsoft Sharepoint, or Atlassian’s Confluence. Trust in the results surfaced by a search solution is of paramount importance. Good data with quality and timely indexing ensures that employees can trust search results. Bad data will result in bad search results, destroying trust in the search solution and will result in little to no utilization or operational gains. Part of building trust, beyond data, is considering the end-users’ digital experience.

The search experience must not be dependent on a separate or altogether different digital experience, like a new internet browser or stand-alone application, to enable search and deliver results. Queries and results must be delivered within software already utilized daily in the workflow, such as Slack or other chatbot interfaces already utilized day-to-day. This continuity of digital experience more effectively enables end users to adopt and leverage a search solution and drives accessibility. Reducing the barrier to entry and ensuring ease of adoption helps businesses recognize greater and faster solution value.

The value of Enterprise Search used to be exclusive to large companies and organizations. However, as Enterprise Search rapidly evolves, all business sizes and industries will be able to see material organizational value. The most impact Enterprise Search will have on small businesses is reducing data silos and optimizing cloud document management - especially as cloud service providers and document storage locations proliferate. Leveraging Enterprise Search will enable smaller companies to scale more efficiently and effectively - ensuring that data driven decisions are not slowed by access to information or stale details. Enterprise Search Software's impact is not limited to just sales, marketing or engineering teams, Enterprise Search brings businesswide to enable more impactful cross-functional work, drive information accessibility, and enhance data-based decision making. Reduce data silos and increase access to information across the organization to support data-driven decisions.

Helping drive the realized value of Enterprise Search for small and mid-market businesses is the reduced need for IT support and active system management. When picking an Enterprise Search Software it is imperative that business users can deploy, leverage, and maintain an Enterprise Search Solution without the involvement of IT resources for integrations, deployment, or  Reducing time, complexity, and soft costs associated with managing and supporting an Enterprise Search Solution will help businesses of all sizes see a clear return on spend. 


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Enterprise Search Engines

Most organizations want an “easy button” to surfacing information, results, and actionable insights - Enterprise Search Software is absolutely the turnkey solution. But as recognized previously, Insight Engines include Enterprise Search Engines which contain actual infrastructure and databases. Engines are software packages that are deployed in the cloud, or on-premise, and require active management, support, and maintenance from a dedicated IT or devops team. Separating out the Software from the Engines, there are various providers for search engine technology both open-source and proprietary. Ultimately, these systems require a large investment of resources, time, and energy to support and maintain. These tools can drive significant positive impact for organizations as the engine hands finite control of a search engine infrastructure over to you, the end users. Unfortunately these search engines can be incredibly complex and difficult to support. Integrations must be built and manually supported, while user-interfaces and the final digital experience require maintenance as well. 

Two of the most popular open-source engines are Apache's Solr and Elasticsearch. Both are powerful and have the ability to classify, index, and deliver search results. But both require demanding cloud server solutions to run and operate at the scale necessary to drive impactful results throughout an organization. Search Engine providers do have options for supplemental managed service packages, but those require additional financial investment to leverage effectively. Around each corner with Enterprise Search Engine providers are hidden hosting, management, maintenance, and managed service costs. 

Solr is a solution, built on top of the Apache Lucerne library, and is primarily developed and deployed to handle structured data. This is a relevant tool for organizations that have standard, repeatable data sets that might not see frequent changes. However, in modern businesses data is always changing and data repositories continue to drive towards less structure for adaptability. 

Elasticsearch, while a larger package and also built on Lucerne, includes some features that make it more scalable and robust for unstructured data. Elasticsearch supports complexity and is the better of the two open-source enterprise search engines at managing large, unstructured data sets. This horizontal scaling enables Elasticsearch to support more nodes than Solr. 

A non-insignificant consideration in differentiating between Solr and Elasticsearch is the community support. Both are considered open-source so there is a considerable community following for both packages but, Elasticsearch is the more popular of the two. With greater popularity comes greater community engagement which can help partially reduce the burden of managing the search infrastructure. 

While both Solr and Elasticsearch provide the mechanisms to index and deliver search results, they have to be managed and supported to ensure the solutions remain effective after implementation. Elasticsearch has popularized the ELK Stack while Solr remains a bit more open-ended from a server and infrastructure management perspective.  Both engine providers require technical and IT expertise to manage, deploy, and scale effectively. Many organizations find it is easier to leverage a managed solution and deploy Enterprise Search Software.

Both Solutions and Engines provide the technology and results to deliver internal search results throughout an organizations. Engines require a great deal of work and technology, let alone the technical expertise to setup and maintain. Enterprise Search Solutions, like Arrchiver, are purpose-built to deliver contextualized answers in the flow of work from internal data sources. Easy to implement, easy to integrate, and easy to maintain - deliver search results in the flow of work and eliminate data silos.