We recently announced our Series C funding, a major milestone that will fuel Cast AI’s ongoing innovation and product expansion. Today, we’re excited to launch Database Optimizer (DBO) – an automated caching solution designed to streamline database performance and simplify operations.
Databases are the backbone of modern applications, but managing their performance and scalability can often feel like navigating a minefield. Challenges such as maintaining efficiency, scaling workloads, resource optimization, and ensuring consistent performance constantly strain operations teams. Traditional caching methods, although helpful, often add layers of complexity and significant overhead.
The database optimization challenge
As applications grow, databases inevitably face heavier loads, leading to sluggish performance, increased complexity, and complex infrastructure management. Traditional caching solutions like Redis or Memcached typically require significant engineering effort, including manual cache management, custom coding, and frequent adjustments. Infrastructure teams are often stuck between overprovisioning resources and risking poor performance under heavy loads.
Moreover, dynamic environments lead to frequent cache invalidation issues, where stale data can disrupt application reliability. Scaling databases through read replicas or larger instances becomes complex and unsustainable in the long run.
Meet DBO: Simplicity through automation
DBO sits between your application and its database, acting as an intelligent, no-code caching layer. When a query arrives, DBO lets it pass directly through to the database. Subsequent identical queries are intelligently cached by DBO, dramatically reducing database load and latency.
The solution continuously monitors data traffic and dynamically manages Time-to-Live (TTL) values based on query frequency and underlying database changes. Whenever an update or change is detected, DBO automatically invalidates relevant cached data, maintaining consistent and fresh query results.
DBO operates transparently as a database proxy, intercepting requests at the network protocol level. It inspects incoming queries and responses directly from the application, intelligently caches query results, and tracks database changes through real-time monitoring.
This real-time traffic inspection method enables DBO to decide precisely when to cache and when to invalidate cached results, ensuring high data accuracy and reduced latency. Such a detailed, transparent approach allows DBO to deliver superior performance without modifying existing applications or additional infrastructure layers.
Automated caching and invalidation, built for modern workloads
DBO utilizes a data-driven caching algorithm to ensure optimal performance and data freshness. Each database query response is analyzed for cache suitability, with caching decisions based on the frequency and consistency of queries. The smart invalidation mechanism continuously monitors changes at the protocol level, automatically invalidating affected cached entries whenever a database update occurs.
Why DBO stands apart
- Zero-code implementation: DBO requires no changes to your existing application code.
- Simplified setup: Connect your cloud account and deploy DBO within Kubernetes using an easy-to-run deployment script.
- Automatic cache management: Intelligent caching and invalidation happen automatically, eliminating manual cache management.
- Transparent operation: DBO operates as a seamless proxy, ensuring minimal complexity and optimal performance.
- Enhanced query observability: Quickly identify high-impact queries, slowest queries, cacheable queries, and total query volume.
Immediate impact and long-term benefits
With DBO, customers experience significantly reduced database load, enhancing application performance and responsiveness. This optimized performance ensures applications scale smoothly under increased traffic, eliminating concerns related to resource provisioning. Additionally, DBO proactively caches emerging critical queries, removing the need for application re-architecture as workloads evolve.
When testing DBO internally, we observed a strong correlation between database CPU usage and the DBO cache hit rate. The image below shows an example using our internal inventory database, which tracks various instance types across multiple cloud providers. Queries executed on this database are typically compute-intensive, as they often involve filtering for instances based on specific criteria, such as the number of CPU cores, region, availability zone, and more.
These queries are run at a high frequency, even though the underlying data doesn’t change often, it’s only synced periodically. With DBO enabled, we observed that an increased cache hit rate led to a noticeable reduction in database CPU usage.
Early feedback and future roadmap
Early adopters have highlighted the ease of setup and immediate performance improvements as standout benefits.
One of the toughest challenges with database caching—especially in distributed systems like ours—is cache invalidation. But with Cast AI’s DBO, it just works right out of the box.
We’re now seeing cache hit rates of 80–90%, which is outstanding. On I/O-bound servers, cutting database hits by 90% has a huge impact—it saves money and significantly improves performance.
Our services were already pretty fast, but DBO shaved off an additional 100 milliseconds, which makes a noticeable difference. If you’re thinking about adding a cache, DBO is an easy choice.
Julius á Rógvi Biskopstø, CTO and Co-founder at Flowcore
As we evolve DBO, our roadmap includes enhanced support for complex queries and stored procedures, identifying inefficient queries and automatically improving performance, better query indexing, and expansion to additional database types.
Get started today
Ready to optimize your database performance without the usual headache? Explore how DBO can effortlessly streamline your database operations. Learn more about DBO in our documentation.
4.8/5 60+ reviews
