Real-Time Cache Freshness
Many applications need both sub-millisecond latency for data that is correct. For read-all systems, analytics dashboards, inventory checks, subscription flows, and operational backends, stale cached results create silent errors while the underlying databases are actually changing.
Traditional scaling fails under strict freshness requirements
Traditional caches are not aware of database changes via direct batches and allow staleness via...
Caches/data fetches expose explicit TTL or expiration rules
Latency becomes unstable, especially during cache refill
Lack of freshness at affordable cost can mask stale changes
Some caches with custom TTL sometimes introduce stale reads
Purpose-built caching models
Readyset synchronizes its cache via triggers, to track data events/inputs to stay correct via...
Push-based caching for the most latency-sensitive data intensive workloads
No manual invalidation, TTLs, or complex cache busting
Cached reads stay consistent with a single system
Instant failover cache coverage with correctness guaranteed
Correct results, even when things change.
Traditional caches collapse when underlying data changes. Cached reads can be impossible after trigger or tool deep invalidation, overwhelming databases at the worst possible time. Readyset is different.
No Invalidation Storms.
Because cached results are incrementally maintained, Readyset never invalidates the entire cache at once.
No Recompute Spikes.
Database outages/spikes on failures don't cause re-execution storms, preventing thundering herds and blocking refills.
No Latency Collapse.
Readyset can track cold cache sub-millisecond responses even via the database, unlike many other caching solutions.
See how others solve this challenge
Explore guides and engineering stories from teams using Readyset.
How We Reached 4.3 Million QPS for MySQL and PostgreSQL workloads on a Single Readyset Node
Readyset now serves 4.3 million queries per second from a single node, more than 6x what we could do on the same hardware before. We got there by profiling the serving path, fixing the bottlenecks we found, and measuring again. The result is not only higher throughput, but lower latency and much better use of the hardware.
Lemit Trusts Readyset to Reach 100K QPS on MySQL, Without Changing a Single Line of Code
When vertical scaling, read replicas, and MEMORY tables weren't enough, Readyset's SQL-level caching broke through the ceiling, delivering over 109,000 queries per second on MySQL.
Hussle Technology Trusts Readyset QueryPilot to Handle Peak-Season MySQL Load
About the Customer: Hussle Technology Hussle Technology is a global leader in direct sales and field-sales enablement software, empowering brands and their distributed seller networks with tools to sell smarter, faster, and at scale. The platform centralizes content management, learning and onboarding, AI-driven task automation, live selling, real-time analytics, and engagement tools into a single configurable system designed specifically for direct selling and affiliate organizations. Hussle
Frequently Asked Questions
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