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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 new release of SymmetricDS 3.0 will help you:
The data loader subsystem was refactored to support JDBC batch updates and fast path loading outside of JDBC. A pluggable interface allows for vendor-specific implementations of loading data. PostgreSQL and Greenplum are the first dialects with extensions to bulk-load data. We plan to add more implementations in the future. All dialects benefit from the stream-lining of the data loader code and use of batch updates.
Syncing with multiple nodes in parallel is nothing new when you have a group of nodes pushing to a single node, but now the concurrency can originate from a single node. With concurrent synchronization, you control a pool of threads for performing pushes or pulls in parallel with remote nodes. Monitor how many nodes are being synced from a central node and adjust the pool according to network and database conditions.
When two or more nodes update the same data at the same time, now you can determine which update wins and propagates across the nodes to keep data consistent. One of five detectors are configured at the table, channel, or node group level to watch for conflicts. A resolver is configured to decide which row wins during a conflict. If one of the four resolvers doesn’t meet your needs, use the Java API to write a custom one. A manual resolver is provided that will put the batch in error for the user to resolve from the console.
Android mobile devices are now supported for change data capture and data loading. Mobile applications that use a database can include the SymmetricDS Pro library to automatically keep the database in-sync with remote nodes. Developers can write to the device’s database and let SymmetricDS Pro handle the problem of efficiently syncing data.