Big data and Hadoop have come to be closely associated with each other. "Big data" refers to the diverse and rapidly expanding data sets that strain the traditional infrastructures and processes of today's organizations. These data types includeunstructured data such as documents, images, video, log files and social media content, as well as structured data in conventional databases. Hadoop is an integrated group of Apache open source software technologies that allow for storing and analyzing big data in clusters of off-the-shelf commodity servers. Hadoop's powerful distributed processing, cost-effectiveness, and early domination of the big data analytics market have led many people in the corporate and public sector IT worlds to think of big data and Hadoop as a natural combination, like peanut butter and chocolate.
While big data and Hadoop may be perfectly paired, working with them poses challenges around moving big data into a Hadoop cluster and managing the data once it's there. Fortunately, technologies from Qlik (Attunity) nicely solve both of these challenges.
Qlik (Attunity) is a leading maker of database replication software and big data integration solutions. Businesses looking to maximize their return on big data and Hadoop choose Qlik Replicate (formerly Attunity Replicate) to implement their big data ingestion workflows because Qlik Replicate (formerly Attunity Replicate):
With Qlik Replicate (formerly Attunity Replicate) you can efficiently ingest data from nearly any source system into a Hadoop cluster. Once data is in the cluster, use Qlik Visibility (formerly Attunity Visibility) to help manage and optimize your Hadoop environment: