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Cloud-native POS platform for seamless omnichannel customer experience.
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A single hub for all promotions campaigns.
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The most advanced synchronization solution for databases and file systems.
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Data configuration and batch automation across different disparate systems and vendors.
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Cloud-native POS platform for seamless omnichannel customer experience.
![]()
A single hub for all promotions campaigns.
![]()
The most advanced synchronization solution for databases and file systems.
![]()
Data configuration and batch automation across different disparate systems and vendors.
The initial data load is an important first step for data replication, so in the latest version 3.10 of SymmetricDS Pro, we worked hard to improve the Outgoing Loads screen to make it easy to follow progress and see how long the load will take. Here are some highlights that benefit long-running loads.
Found under Manage -> Outgoing Loads on the menu, this screen has been the place to go for a summary of data loads. In SymmetricDS Pro version 3.10, it has some new summary statistics and new buttons. First, you’ll notice it shows the number of tables and rows for the load, which is much easier to think about than batches. It also has a progress bar with a percent complete, based on the number of rows loaded so far. Instead of switching to the Nodes panel, there’s a “Load Data” button right here to start a new partial or full load.
By clicking on the magnifying glass icon, it opens a view consisting of mini panels of information about the load, each one updating with every refresh interval.
There’s a lot of information on the screen, so let’s describe each of these mini panels:
The enhanced Outgoing Loads screen answers the questions we’re continually asked during projects. Questions like, “How long will the data load take?” And also “What table is being loaded right now?” While we’re used to thinking about batches for SymmetricDS, summarizing data load progress in terms of tables and rows is more familiar to users. We’ve tried to make your first encounter with data replication a good one, but we’re always open to ideas to make it better, so let us know what you think!

