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SingleStore Flow Released
February 13, 2025
SingleStore announced the launch of SingleStore Flow, a no-code solution designed to greatly simplify data migration and Change Data Capture (CDC).
The no-code interface allows users to select the tables and data they need to migrate through a user-friendly point-and-click experience. By eliminating the need for manual scripting and extensive monitoring, SingleStore Flow significantly increases productivity, reducing the time, cost and disruption often associated with data migration and CDC setup.
It seamlessly integrates with source-related databases – including Oracle, SQL Server, PostgreSQL and MySQL – and comprises two components: SingleStore Ingest, which handles initial migration for tables up to 10GB, as well as ongoing CDC; and SingleStore XL Ingest, which manages the initial migration of larger tables by segmenting them to ensure timely and seamless transfer of large datasets.
“AI and real-time analytics move at the speed of now, and data migration and integration needs to match that flow,” said Eric Hanson, Director of Product Management at SingleStore. “By simplifying and streamlining the process of using data for real-time and AI applications, SingleStore Flow jumpstarts the ability to try new use cases and enhance existing applications. It’s especially helpful for companies seeking to move from a legacy relational database to a modern, scalable platform adept at real-time analytics.”
SingleStore Flow is a subset of SingleConnect, the company’s overall data integration experience. SingleStore Flow includes new tools acquired via the acquisition of Australian data integration platform BryteFlow in late 2024.
Key Capabilities of SingleStore Flow:
- Log-Based Change Data Capture (CDC): Captures and replicates data changes in real time, ensuring target databases remain synchronized with source systems.
- Flexible Scheduling: Offers options for real-time or scheduled data transfers to accommodate various operational requirements.
- Automated Schema Creation: Automatically generates corresponding tables in the target database, streamlining the migration process.
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