Data has become an ever increasing crutch in our daily lives and drives more and more business decisions than ever. With the steady increase in data storage technologies consumers are faced with greater challenges to keep the data synchronized for accurate reporting, analysis, and overall processing. Traditional databases such as SQL Server, Oracle, Postgres, and MySQL still play a major role in many companies. However with the rise of the cloud platforms and NoSQL technologies commonly used for warehousing and analytics the need to support a variety of technologies within each business is important.

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Load testing of database replication finds the upper limit of how well the system can perform, and it provides assurance that replication will make it through times of peak usage. Let's look at how to simulate production activity for SymmetricDS data replication in a lower environment so you can deploy with confidence.

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Common batch mode was enhanced in SymmetricDS 3.11 to allow any group of nodes to share batches. Let's look at what common batches are and why this is a big deal for database replication with more than a couple nodes.

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Subsetting data during replication can improve the overall performance of your sync scenario and reduce the size of target databases.   This article will explain some of the ways SymmetricDS will allow you to subset your data and how to consider the performance implications with each case.

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SymmetricDS was originally designed to support a use case with numerous client nodes spread out geographically in order to replicate to a centralized server.  The out of the box properties and configuration are optimized to support many other use cases and may not be sufficient when you need more than a couple dozen client nodes.   Check out some of the helpful hints below to assist in a successful synchronization rollout to numerous clients.

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