Search technology has profoundly changed the way we access information, they way we learn, the way we work — in essence, the way we discover what’s true. Not surprisingly, search is central to the success of almost any enterprise, these days. To handle big data effectively, a search solution must combine high speed with scalability. Enter Apache Solr™, the popular Java-based open source search platform. It provides search functionality for some of the world’s largest Web sites. In DataStax Enterprise a unique implementation of Solr makes it an even better platform for delivering transformative enterprise search capabilities.
“I’d been looking for a ‘holy grail’ solution to fit our big data needs, and full text searching appeared to be the missing link. Large database vendors were not able to provide us with cost-effective solutions. When DataStax came out with support for Solr in DataStax Enterprise, we felt we had found the solution we were looking for.”
Why Apache Solr?
Search is one aspect of big data that everyone can relate to. We’ve come to expect that when we type text into a box and click “search,” we’ll get the results we’re looking for in a fraction of a second. That’s true whether you’re shopping online for the perfect pair of hiking boots, using your smartphone to get directions to the appointment that started five minutes ago, searching anxiously for the right specialist for a seriously ill child or needing the latest KPIs for the report due at five o’clock. With its distributed scalability, high performance and ability to handle virtually any type of data, no search solution does a better job of tackling today’s diverse enterprise search requirements than Apache Solr.
Solr’s key features include:
- Robust full-text search and hit highlighting
- Faceted search (e.g. by manufacturer, brand, type, size, price, etc.)
- Rich document handling (e.g., HTML, Word, PDF, RTF, email, .zip files, and audio and video formats)
- Geospatial search (i.e., combining location information with data. Includes filtering results by distance, even filtering spatial data within documents, such as CAD drawings or blueprints)
Want to see what the power of Apache Solr can do for your applications? Get it with DataStax Enterprise.
How we make it even better
The distribution of Apache Solr you receive with DataStax Enterprise provides numerous enhancements over native open source Solr. Through integration with Apache Cassandra, Solr gains valuable big data capabilities that make it an even stronger platform for enterprise search, including continuous availability, real-time functionality and data durability.
With enhanced Apache Solr in DataStax, you get:
- Continuously available Solr search – Unlike standard open source Solr, the implementation in DataStax Enterprise scales more effectively and more easily (add a node online in just minutes with DataStax OpsCenter) and it can never go down. It’s able to take advantage of Cassandra’s distributed architecture, which ensures continuous availability with no single point of failure.
- Real-time search – DataStax brings real-time functionality to Solr search through its integration with Cassandra, an essential benefit in a Web 2.0 world and not possible with native Solr.
- Data durability – With the community version of Solr, data can get lost. In the version that comes with DataStax Enterprise data is always completely safe, thanks to the data durability features of Cassandra.
- Seamless integration across mixed workloads – Integration with Cassandra’s real-time data functionality and Hadoop batch analytics brings Google-like performance to your database. And you get the added benefit of not having to implement time-consuming and error-prone ETL data movement routines.
- And more – With Solr in DataStax Enterprise you also get scalable and performant write operations across multiple datacenters and the cloud, automatic data sharding, and easy index rebuild operations, none of which are available in native Solr.
Experience enhanced Solr for yourself. Get it today with DataStax Enterprise.
Scenarios it transforms
Here are some of the ways enterprises can deliver better search experiences using integrated Solr enterprise search in DataStax Enterprise:
- High volume Internet and intranet site searches – Our implementation of Solr enables extremely fast site indexing and searching. It provides all of the core Solr benefits, including autocomplete, spell check, “more like this” functionality, support for natural language processing and wildcards, and many others, while gaining continuous availability and real-time processing provided through integration with Cassandra.
- Full text search across diverse document and file types – Solr enables organizations to rapidly locate valuable information strewn across a wide assortment of document types, including PDFs, Word documents, emails, web pages and many others. Our implementation of Solr has improved the text search process for Healthx and our integrated Solr capabilities proved to be an ideal solution for HealthCare Anytime.
- Log processing and application code search – IT teams can quickly search extremely large application log files to speed development or troubleshoot problems. Open source specialist SourceNinja uses the integrated Solr search capabilities in DataStax Enterprise in the mammoth task of monitoring and tracking all open source software applications across all platforms.
- Categorized (faceted) search – With Solr, any organization can economically gain the same search capabilities of the largest online retailer. It allows people to find exactly what they need faster by filtering results into logical categories, or facets, for example by manufacturer, product type, key features and the like. It narrows results further still into sub categories such as price or color. And it can instantly display the number of items available within any given parameter.
- Location-aware big data applications – Solr offers powerful geospatial search capabilities that bring location awareness to a host of big data applications. As with text search, results can be categorized through facets (e.g., by distance, city or neighborhood). Solr also combines geographical information with text parameters, which allows people to sort results using descriptions such as “restaurants with children’s menus” or “rooms with ocean views.”