Big Data Structured Search
|Open Source||Using Apache 2.0 license|
|Robust||Database-like query capability|
|Fast||Sub-second response times|
|Available||Handles hundreds of concurrent queries|
|Scalable||Adjusts to fit the size of your data|
|Durable||Survives multi-node failure w/o data loss|
Blur is an open source search engine capable of querying massive amounts of structured data at incredible speeds. Rather than using the flat, document-like data model used by most search solutions, Blur allows you to build rich data models and search them in a relational manner similar to querying a relational database. Using Blur, you can get precise search results against terabytes or petabytes of data at Google-like speeds.
Working hand-in-hand with Hadoop, Blur also also gives you the ability to correlate structured data in complex and meaningful ways. Here’s an example of the kind of query you could perform with Blur using data from the US Census: show me all of the people in the United States who were born in Alaska between 1940 and 1970 who are now living in Kansas.
Where does Blur fit into the big data stack?
- At the top
- User focused
- The result of big data crunching
- Tight integration with Hadoop