Data Synchronization

The purpose of data synchronization is to maintain the consistency of data contained in several applications, databases or systems.

What is Data Synchronization?

Many cases exist in the information system where data is managed separately by multiple applications or databases, yet needs to be kept consistent between these systems. The need for data synchronization can either be permanent (synchronization between operational systems), or temporary (for example during a migration). Synchronization can be either mono-directional or bi-directional.

Data synchronization includes all the processes that maintain data in sync between the applications and databases.

Challenges of Data Synchronization

There are numerous challenges to implementing efficient and reliable data synchronization processes.

• Data synchronization often involves low latency processes which must tend toward real time. It is thus critical to restrict the volumes of data processed to reduce the processing time.
• Environments involved are heterogeneous and often combine legacy systems, packaged applications, RDBMS, mainframes, files, etc. Data structures vary widely in all the systems that need to be maintained in sync. These differences entail complex mappings between sources and targets, as well as aggregations, calculations, etc.
• When conflicts of data occur, they must be managed and resolved taking into account record update precedence or “record owner”.

Open Source Data Integration Solutions for Data Synchronization

Talend´s data integration solutions are optimized for enterprise-grade data synchronization. The following features are especially critical to the design, development, execution and maintenance of data synchronization processes:

• Business-oriented process modeling that involves business stakeholders and ensures proper mapping of data integration processes to business processes.
• Fully graphical development environment that greatly improves productivity, facilitates maintenance and ensure reusability of data mappings and transformations.
• Highly scalable and fast execution platform with a grid approach that enables the processing of data close to its source and target.
• Broadest connectivity to support all source and target systems.