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.
109KQueries Per Second
0Lines of Code Changed
<1msCached Query Latency
8xRead Throughput Increase
Before and after Readyset
Metric
Before Readyset
After Readyset
Read throughput
~13K SELECTs/sec hitting MySQL directly
109K+ QPS across the stack
Cached query latency
Reads served by InnoDB, competing with writes
Sub-millisecond from Readyset
MySQL primary load
All reads competing with 26K INSERTs/sec
Primary freed for writes only
Application code changes
MEMORY tables and manual caching workarounds
Zero, drop-in via ProxySQL routing
The challenge
The solution
The results
"Using Readyset with our existing MySQL infrastructure allowed us to combine hardware and software to get the most out of our setup. That gave us predictability and stability during spikes in our workload. Our concerns about the database not being able to keep up when we need it the most are now a thing of the past."
Juliano Missiagia, Co-founder, Lemit
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Lemit's data enrichment platform powers real-time credit decisions for businesses across Brazil, processing individual lookups, batch enrichments, and API queries against millions of records. The workload is highly sensitive to latency. Every millisecond matters when clients are waiting on credit decisions. The codebase was mature with no room for application changes, and the production workload was impossible to reproduce in QA.
The team had already exhausted conventional approaches to scaling MySQL:
Aggressive tuning of OS and MySQL parameters on Percona Server for MySQL
Async read replicas for redundancy and OLAP offload
MEMORY engine tables for fast in-memory lookups, but these lacked persistence, transaction support, and used table-level locking
Massive vertical scaling to 256 virtual processors (2× AMD EPYC 7713 64-Core, 128 physical cores with hyperthreading, dual NUMA nodes), 1.4 TB of DDR4-3200 RAM, and a tiered XFS storage layout (14 TB data, 6 TB binlog, 1 TB redo) served from a Dell EMC Unity XT 380F All-Flash array over Fibre Channel
Despite this investment, read queries were still competing with writes for the same InnoDB buffer pool and CPU cycles. The database was better resourced than ever, but throughput had plateaued. Lemit had reached the ceiling of vertical scaling.
The team needed a solution that could dramatically increase read throughput without any application code changes, and without the limitations of MySQL's built-in caching mechanisms.
Lemit deployed Readyset as a transparent, wire-compatible caching layer in front of their MySQL primary. Unlike traditional caching solutions that require application changes, cache key management, and manual invalidation, Readyset operates at the SQL protocol level, which makes it completely invisible to the application.
Readyset intercepts read queries between the application and MySQL, caching results at the SQL level. No Redis, no Memcached, no application-level cache keys to manage.
Cached results are incrementally updated via the MySQL binlog as underlying data changes. No TTLs to configure, no stale data, no manual invalidation logic.
Readyset was deployed alongside the existing MySQL primary and replica, with ProxySQL providing intelligent query routing. ProxySQL analyzed each query's digest and routed it to the optimal backend:
Traffic Type
Routed To
Why
High-volume read queries
Readyset (port 3309)
Sub-millisecond response from cache
Writes / DML
MySQL Primary (port 3307)
Strong consistency required
Analytical queries
MySQL Replica (port 3312)
Offload from primary
With 16 query rules configured in ProxySQL, the highest-volume read patterns (accounting for hundreds of millions of hits) were directed to Readyset. The cache absorbed the vast majority of read traffic before it ever reached MySQL.
Readyset works with any MySQL or PostgreSQL application: no code changes, no ORM modifications, no migration required.
Lesson 1: Adaptation and experimentation are essential. Each phase of Lemit's journey built on learnings from the previous one. There was no single "right answer" from the start. The architecture evolved through testing and observation.
Lesson 2: Conventional scaling has a ceiling. Readyset breaks through it. Bigger servers and more replicas couldn't solve the fundamental problem of reads and writes competing for the same resources. Readyset's SQL-level caching was the architectural innovation that changed the equation.
Lesson 3: Continuous observation is critical. Durability parameters like sync_binlog and innodb_flush_log_at_trx_commit were tightened later as deliberate safety choices, trading some write throughput for stronger crash guarantees. Percona PMM monitoring the entire stack (including Readyset) was essential for quantifying the performance cost of those choices and confirming that the workload could still hit its SLAs.
Readyset now operates as a core performance layer in Lemit's stack, ensuring their MySQL infrastructure delivers the throughput and latency their application demands, today and as traffic continues to grow.
Lemit (Lemit Tecnologia da Informacao) is a Brazilian data enrichment and credit intelligence company based in Sao Paulo. Their platform enables businesses to make faster, more accurate credit decisions by enriching, qualifying, and cleansing customer data at scale, powering individual lookups, batch integrations, and real-time API queries across millions of records with 100% all-flash storage.
