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.

Big Data and Hadoop Challenges: Big Data Ingestion into Hadoop

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):

  • Provides a universal solution for replicating data from nearly any type of source system (relational database, data warehouse, mainframe, file system, SAS application) to any major Hadoop distribution (such as Cloudera, Hortonworks, MapR, or cloud-based Hadoop platforms like Amazon EMR). With Qlik (Attunity) you can implement a wide range of data flows, such as Oracle to Hadoop data migration or Teradata EDW offloads to Hadoop, all through one unified data integration platform.
  • Empowers data architects and data scientists to configure and execute big data ingestion flows through an intuitive graphical interface, without having to do any manual coding.
  • Provides central control over and visibility into all your big data and Hadoop integration jobs, including progress monitoring and configurable alerts and notifications.
  • Supports real-time data integration flows based on change data capture technology, as well as high-performance bulk data migration.

Big Data and Hadoop Challenges: Managing Big Data in Hadoop

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:

  • Gain real-time insight into usage patterns and trends for the storage layer and processing layer within your Hadoop data warehouse, so you can identify current or potential bottlenecks and plan ahead for adding disks or nodes.
  • Break down Hadoop resource usage by applications and user groups so you can measure the return on your organization's big data and Hadoop investments and implement chargeback or showback to lines of business.
  • Maintain visibility into Hadoop data access patterns by user groups and individual users, in support of compliance and governance requirements.