By Timo Selvaraj
SearchBlox 8.4 has enabled access to Hadoop, NoSQL and Cloud storage through the Apache Drill connector with the database collection. Apache Drill supports a variety of NoSQL databases and file systems, including HBase, MongoDB, MapR-DB, HDFS, MapR-FS, Amazon S3, Azure Blob Storage, Google Cloud Storage, Swift, NAS and local files. A single SQL query can join data from multiple datastores to provide a unified view of the data. Once the data is indexed by SearchBlox, it can be made available for search and visualization similar to other databases like Oracle and MySQL. For example, you can now join a user profile collection in MongoDB with a directory of event logs available within Hadoop.
#1 Use SQL for access to non-relational data
Ability to use familiar SQL queries to access data from data stores simplifies the need to learn additional skills for managing the data. Ability to combine the data between multiple non-relational data for search and visualization of information.
#2 Ability to search at a very high speed for large volumes of data
SearchBlox enables you to access the data within Hadoop or other big data storage for indexing and search. Once the data is indexed, faceted search can be enabled based on the available fields for large volumes of data for full text search.
#3 Visualization made simple for NoSQL and Cloud Storage
The visualization module provided SearchBlox can create time based charts for analyzing various sources of unstructured and structured data in real time. Your customers will not have to understand the challenges of accessing big data using custom queries or complex skills. Access your big data through visualizations.
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