By Stephanie Simone
How do you modernize and build next-gen financial applications when business and regulatory requirements keep your databases anchored on-premises or deployed across multiple clouds?
DBTA recently held a webinar, Revolutionizing Financial Services Databases with AlloyDB Omni, with Greg Frein, database sales specialist for financial services atGoogle Cloud and Sridhar Ranganathan, Product Manager for AlloyDB Omni at Google Cloud, who discussed how AlloyDB Omni brings Google Cloud’s advanced PostgreSQL compatible database power directly to secure, air-gapped environments—letting you modernize legacy workloads and deploy highly secure GenAI apps exactly where data lives.
According to Frein and Ranganathan, financial services companies face continued pressures in the race for business transformation. Now more than ever financial services workloads need to be reliable, standard based, responsive, offer price performance, security, and flexibility.
Customers are looking into open standards based databases to:
- Modernize legacy databases
- Develop cloud-native apps
- Optimize costs
- Deploy cloud-scale apps
- Build differentiated applications
AlloyDB for PostgreSQL is a fully managed, next generation, unified database service on Google Cloud, Frein and Ranganathan explained.
AlloyDB enhancements to standard PostgreSQL include:
- Kernel and performance: Optimized kernel and query execution engine delivering up to 2x transaction throughput and 100x faster analytics than standard PostgreSQL.
- Intelligent analytics: Built-in columnar engine and optimizer changes automatically accelerate analytical queries without application code changes.
- Advanced Vector Search: Integrated vector support and index tuning for building high-performance GenAI applications directly within the database.
- Enterprise Reliability: Built-in availability and reliability with Google provided support and automated patching capabilities for enterprise peace of mind.
- Google support and ecosystem: Direct Google Cloud support expertise (same as GCP) to get faster resolution. And Vertex AI integration for model inference.
For the full webinar, featuring a more in-depth discussion, Q&A, and more, you can view an archived version of the webinar here.