MySQL is too slow? Why you should try MemCP for heavy aggregation workloads

When classic row-store databases become a bottleneck, an in-memory columnar engine can be the performance jump you need.

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If you’ve ever typed “MySQL is too slow” into a search box, you’re not alone. Many applications start on MySQL and then hit a wall when analytics, aggregation, or mixed OLTP/OLAP workloads grow. The obvious fixes — indexing, query tuning, sharding — help, but they don’t always address fundamental storage-model limits. Also Scale-Out-Proxies and Load Balancers do not help.

Enter MemCP: an open source, in-memory, column-oriented database developed to tackle just these pain points. MemCP is designed for modern web services and microservices that need fast aggregation and low-latency access while remaining easy for developers to adopt.

Why MemCP helps when MySQL struggles

• Columnar storage: aggregations and analytics run much faster on columnar layouts because only the needed columns are read and processed.
• In-memory engine: avoids costly disk I/O for hot datasets, giving large speedups for real-time queries.
• MySQL-compatible front end: makes experimentation and migration easier — you can keep familiar tooling while testing MemCP on heavy queries.
• Small base footprint: MemCP’s docs describe surprisingly modest base memory requirements for the system itself, making it easy to spin up test instances.

Real-world approach

1. Identify the slow queries in MySQL (slow query log, EXPLAIN).
2. Prototype those reports/aggregations on MemCP using the same SQL patterns.
3. Compare latency and resource usage (MemCP documentation includes comparative benchmarks).
4. If results look good, consider a hybrid architecture: keep MySQL for transactional durability and use MemCP for analytics and heavy read queries.

Try it out

• Project site/Docs: https://memcp.org
• Source code and README: https://github.com/launix-de/memcp

MemCP is already documented with deployment instructions, examples for microservices integration, and comparison writeups versus MySQL. If you’re battling slow analytic queries today, it’s worth a quick proof-of-concept — the performance gains for aggregation workloads can be dramatic.

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