Before 2019, crawling through in-house networks needed robust components with state-of-the-art architecture to get results quickly and efficiently. The Google Search Appliance was the right tool for the job, but the hardware factor gave it some sizable limitations. Since its move away from physical platforms to the cloud, several alternatives have sprung up to take its place. A quick breakdown of Google’s commercial hardware and its digital replacements may help you determine which option works best for your business.
What Was Google Search Appliance?
Early on, Google’s overarching business strategy was to facilitate in-house searches of local network resources. Originally pioneering Google Desktop, the tech giant soon discovered that relying on customer machines may severely limit the capabilities of their search infrastructure. As such, the company shifted tactics, combining the fluidity of software with the reliability of hardware into a server-based search unit called Google Search Appliance.
Called an “appliance” thanks to its physical nature and proprietary OS, the units exist outside of a business’s own network and would index critical content by crawling through resources, much like the Google search algorithm hunts through web pages today. Data can be categorized and prioritized based on mandated criteria, allowing IT departments to section off results by individual and create a relatively secure method for categorizing and analyzing data.
A proprietary-based server solution may have seemed like a good idea at the time, but as the Google Search Appliance was integrating itself into company networks, cloud-based computing was already on the rise. In addition, the simplicity behind the product’s plug-and-play design didn’t outweigh the negatives. Second-hand units were not covered by Google’s service department, either, making reselling obsolete hardware difficult at best.
When compared with having an obsolete network appliance attached to their servers, companies quickly saw the advantages of sourcing their search functions onto the cloud as well. The death knell for the Google Search Appliance enterprise indexing solution came in early 2016 when the company announced that in two years it would be discontinuing the platform. Instead, the tech giant would urge its customers to seek alternatives based on the cloud.
All instances of the Enterprise version of the Google Search Appliance shut down as of 2020, leaving thousands of businesses scrambling for an alternative that would either perform as well as or better than prior technology. Thankfully, the IT community has come to the rescue with several open-sourced options that can do a lot of what the Appliance could do, and in many cases, they outperform the tech as well! Two of the most popular alternatives include:
Looking for a way to combine all of the enterprise features that companies need to maintain, categorize and track data, the Apache Lucene-based Elasticsearch came forward as a robust system to tackle the most grueling of search tasks. Some of the key features of the platform include:
- Scalability: The system can be updated to analyze gigabytes of data over thousands of servers, future-proofing your search needs.
- Performance: With distributed inverse indices, Elasticsearch can crawl through full-text queries with ease.
- Schema-Free: Working without the need for updating the data definitions found within schema architecture means faster searches and more comprehensive indexing.
Because of its open-source nature, many plugins are available for Elasticsearch that expand its functionality enormously.
Another great enterprise-level option, Solr also works within the Apache Lucene framework to transform it into a search platform. One standout feature is the auto-suggest function allowing a few character inputs to result in a host of suggested search queries. The software also offers multilingual support, making it a go-to alternative the world over. Additional advantages include:
- Speed: Using Java for its functioning, the platform delivers results in less than a second, improving efficiency throughout the organization.
- Compatibility: Solr can run on any platform that is also congruent with Java, as well as indexing that works across multiple platforms.
- In-Depth Data Weight: The search has the capability to score results according to complex parameters, allowing for complex indexing and faster searches.
Making the Right Choice
While Elasticsearch and Solr are the more fashionable options available, they are far from perfect. The United Kingdom switched to Elasticsearch over Solr back in 2021 and is currently looking at a more attractive option in 2022. Even so, these two cloud-based enterprise search solutions far outshine the outdated Google Search Appliance in speed and practicality. Check both platforms for compatibility with your current network while also considering future corporate expansions to find the solution that will transform how your company looks at internal data!