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Early Access Feature

This feature is in early access. It may undergo changes based on user feedback and continued development. We recommend testing in non-production environments first and welcome your feedback to help us improve.

The Database Resourcing Challenge

Managing database resources efficiently is one of the most challenging aspects of modern application infrastructure. Organizations constantly struggle with balancing performance needs against cost considerations, particularly:

• Infrastructure Costs: The expense of maintaining adequate database resources can be significant, especially as applications scale.
• Over-Provisioning: To ensure performance during peak times, databases are often over-provisioned, leading to wasted resources during periods of low activity.
• Connection Pooling: Managing database connections efficiently to optimize resource usage while maintaining performance.
• Scaling Complexity: As applications grow, increased workloads, higher data volumes, more complex queries, and geographical expansion all contribute to scaling challenges.
• Latency Issues: Particularly for globally distributed applications, data latency can significantly impact user experience.

Traditional solutions to these challenges often come with their own drawbacks:

• Database Scaling: Adding read replicas or scaling up database instances can be costly and complex to manage.
• Application-Level Caching: Implementing solutions like Redis requires significant development effort and ongoing maintenance.
• Distributed Databases: While they can help with some issues, they introduce additional complexity in deployment and management.

What Is CAST AI Database Optimizer?

CAST AI Database Optimizer (DBO) is an AI-driven database cache designed to improve query performance, reduce database load, and decrease geographical latency.

As part of the extensive CAST AI product suite, DBO offers fully autonomous caching that requires no code changes, zero configuration, and no tuning. In fact, it can be implemented in minutes with a simple deployment and application config update.

DBO's primary goal is to tackle the database challenges of high infrastructure costs, over-provisioning, and geographical latency issues. It achieves this through smart caching mechanisms that improve query performance and reduce the load on your primary database.

Benefits of Database Optimizer

Implementing DBO in your database infrastructure provides several significant advantages:

• Reduced database infrastructure costs - DBO frees up valuable database resources by caching and serving read traffic, potentially leading to significant reductions in infrastructure spending.
• Increased Query Performance - DBO serves any cached queries at sub-millisecond speed, even for complex queries on multi-terabyte datasets. This results in faster response times and improved application performance. Therefore, any slow queries are served instantly without the load burden on the database.
• Lowered global latency - DBO provides a global edge network so that data can be cached locally to wherever your application is running. Connecting to DBO automatically resolves to the closest Point of Presence, so data is fast everywhere.
• Increased engineering productivity - Unlike other caching solutions, such as Redis, DBO requires no code development or configuration. This removes the requirement for cache design entirely. No data modeling, invalidation design, testing, and observability. Developers can focus on application features rather than scaling their database.
• Simplified Scaling: DBO automatically adapts to increased load as your application grows, reducing the complexity typically associated with database scaling.

By addressing these common database challenges, CAST AI Database Optimizer empowers organizations to build more efficient, cost-effective, and performant database-driven applications.