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FundApps’s journey from SQL Server to Amazon Aurora Serverless v2 with Babelfish
- FundApps is a compliance as a service platform that enables compliance teams to respond efficiently to regulatory change, reduce complexity, and increase certainty of the compliance process.
- FundApps utilized the combination of cloud computing and regulatory expertise to launch the first compliance as a service (CaaS) product.
- FundApps migrated their service from a SQL Server database to cloud-centric solutions of Amazon Aurora Serverless v2 with Babelfish for Aurora PostgreSQL and Amazon S3 to improve service scalability and reduce costs.
- FundApps combined extensive dataset with its clients' positions in the Rule Engine to generate actionable results.
- The Regulatory data service is responsible for ingesting thousands of files daily from various regulatory sources and processing the data for use by the FundApps Rule Engine.
- FundApps overprovisioned resources to handle peak load previously which resulted in cost inefficiency. The migration to Aurora allowed FundApps to use the serverless feature that provides auto-scaling configuration, where the database scales capacity up or down based on the application's needs.
- FundApps used a Babelfish feature for Amazon Aurora PostgreSQL-Compatible Edition to enable Aurora to understand commands from applications written for SQL Server.
- The transition to the Aurora PostgreSQL database, with the strategic use of complementary AWS services and tools, has delivered tangible operational excellence for FundApps with Babelfish and Aurora PostgreSQL-Compatible.
- FundApps migrated from a traditional, proprietary database to an Aurora PostgreSQL database to achieve significant cost optimizations, scalability enhancements, and performance improvements for their workloads.
- The migration from a traditional, proprietary database to an Aurora PostgreSQL database, combined with the strategic use of complementary AWS services and tools, has delivered tangible operational excellence for FundApps with Babelfish and Aurora PostgreSQL-Compatible.
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