Over time, the number of legacy applications developed to support an enterprise’s operations grows significantly. Applications maintained databases of information, but the contents of these databases were typically not exposed for use by other applications that were independently developed.
As companies grew more reliant on their IT resources, it became apparent that many new applications could benefit from use of the data stored in the databases of silo legacy applications. In addition, as companies merged, it became necessary to somehow marry their disparate databases into a common repository of knowledge for the newly merged corporation.
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.
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.
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. All of these systems must intercommunicate with each other in real-time. They must be integrated with a high-speed, flexible, and reliable data distribution and sharing backbone.
Shadowbase Streams for data integration solves these challenges, providing the means to integrate existing applications at the data or event-driven level in order to create new and powerful functionality. Shadowbase Streams seamlessly moves selected data in real-time from a source database to a target database where it can be used by a target application or data analytics engine. As changes are made to the source database (change data capture), they are immediately replicated to the target database to keep it synchronized with the source database (for this reason, “data integration” is often called “data synchronization”). In the process, Shadowbase Streams makes any necessary format changes to the updates in order to meet the needs of the target system. In addition, it can filter updates and eliminate updates that are of no interest to the target system. Data replication is transparent to both the source application and to the target application. Upon delivery, the target application can then make use of this real-time data, enabling the implementation of new and valuable services to enhance competitiveness, to reduce costs or to increase revenue, to satisfy regulatory requirements, and to generally improve the user experience.
Shadowbase Streams for Data Integration and Synchronization supports the following capabilities: