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Data Integration and Synchronization Solutions

Integrate Data for Competitive Advantage

Over time, the number of legacy applications developed to support an enterprise’s operations grows significantly. Applications maintain databases of information, but the database contents are not typically exposed for use by other independently developed applications.

As companies grow more reliant on their IT resources, it is apparent that many are storing data in silo legacy databases. As companies merge, it is often necessary to join disparate databases into a common repository for the new corporation.

There is also big data. The amount of information being generated each year is exploding at an unprecedented rate. It is estimated that 80% of the world’s data was generated in the last two years, and this rate is increasing. Social media such as Twitter and Facebook, articles and news stories posted online, blogs, emails, YouTube and other videos are all contributing to big data.

In today’s 24×7 online environment, having query access to a remote database is not sufficient. Querying for data is a lengthy and complex process, and applications must react far more quickly to data changes than querying allows.

It is necessary for one application to immediately have real-time access to another application’s updated data, just as if that data were stored locally. Furthermore, big data analytics engines require a large network of tens, hundreds, or even thousands of heterogeneous, purpose-built servers, each performing its own specific task. Since these systems must intercommunicate with each other in real-time, they must share an integrated high-speed, flexible, and reliable data distribution network.

HPE Shadowbase Streams

On top of all these applications, there is now big data. The amount of information being generated each year is exploding at an unprecedented rate. It is estimated that 80% of the world’s data was generated in the last two years, and this rate is increasing. Social media such as Twitter and Facebook, articles and news stories posted online, blogs, emails, YouTube and other videos — they are all contributing to big data.

What is needed is a way for one application to immediately have real-time access to the data updated by another application, just as if that data were stored locally. Furthermore, big data analytics engines require a large network of tens, hundreds, or even thousands of heterogeneous, purpose-built servers, each performing its own portion of the task.

HPE Shadowbase Streams for Data Integration and Synchronization supports

Zero Data Loss (ZDL)
  • Elimination of data loss in the event of an outage
  • Elimination of data collisions in active/active architectures (future release)
Master Data Management
  • Uni-directional and bi-directional data synchronization
  • Transformation, filtering, cleansing, and consolidation of data
  • Same (homogeneous) or different (heterogeneous) source and target databases and platforms
  • Data warehouse feeds
  • Real-time data replication
  • Offline and online loading/integration
  • Trickle-feed and batch refreshing
Build Real-Time Event-Driven Applications
  • Rapid and reliable reformation and transference of large data amounts between heterogeneous databases and applications in real-time
  • Data distribution backbone for a big data analytics system
  • Elimination of middleware and application modification