Let's Build PlanetScale from Scratch: A Deep Dive into Infrastructure

The Database Revolution That Never Sleeps

Imagine building a database that could handle millions of queries per second, survive a server meltdown without losing a byte, and let developers sleep soundly at night. That’s the promise of PlanetScale, the serverless MySQL platform that took the tech world by storm. But behind the glossy UI and the Vitess-powered engine lies a grueling infrastructure challenge. A new technical deep-dive, titled Homescale Part 1, published on July 16, 2026, reveals exactly what it takes to build something like PlanetScale from the ground up. Source

This isn’t just another blog post about scaling databases. It’s a raw, behind-the-scenes look at the decisions, trade-offs, and engineering sweat required to replicate a production-grade database infrastructure. The authors describe their journey as a “homescale” experiment — building a PlanetScale-like system in a home-lab environment, but with production-level aspirations. In a world where every startup wants to “move fast and break things,” understanding the infrastructure beneath the shiny surface has never been more critical.

Why Build PlanetScale from Scratch?

The database landscape in 2026 is fragmented. Legacy SQL databases like PostgreSQL and MySQL remain workhorses, but they weren’t designed for cloud-native elasticity. PlanetScale solved this by combining Vitess (the same sharding layer used by YouTube) with a serverless MySQL frontend. But what if you wanted to build your own version? The Homescale project attempts exactly that: create a PlanetScale-like infrastructure using open-source tools.

The material examines the core challenge: how do you make MySQL horizontally scalable without rewriting your application code? The answer, according to the developers, lies in a stack that includes Vitess for sharding, Consul for service discovery, and a custom proxy layer for connection pooling. The article covers the initial architecture decisions, such as choosing Vitess 20.0 over newer forks due to stability concerns, and why they opted for etcd instead of ZooKeeper for metadata storage.

The Infrastructure Stack: Vitess, Proxy, and the Hidden Complexity

Vitess as the Backbone

Vitess is the star of the show. Originally built by YouTube engineers to scale MySQL, it handles sharding, replication, and failover. In the Homescale project, the team installed Vitess on a cluster of three nodes, each running Ubuntu 24.04 LTS. They configured a keyspace called homescale with 8 shards, each containing a primary and two replicas. The authors encountered a critical issue early on: Vitess’s VTTablet processes require careful memory tuning. Without proper limits, OOM (out-of-memory) errors crashed the cluster during load testing.

The Proxy Layer: Where the Magic Happens

PlanetScale’s killer feature is its ability to present a single MySQL-compatible endpoint, even though data is distributed across dozens of shards. The Homescale team replicated this using ProxySQL, which routes queries to the correct shard based on the Vitess VSchema. However, the developers encountered a stumbling block: ProxySQL doesn’t natively understand Vitess’s shard keys. They had to write custom query rules in Lua, mapping WHERE id = ? clauses to specific shards. This added latency but was essential for correctness.

Real-World Lessons: What Went Wrong

The article doesn’t shy away from failures. One major issue was network partitioning. During a simulated network failure, Vitess’s failover mechanism kicked in, but ProxySQL continued sending traffic to the old primary. The result? Data inconsistency and a 20-minute downtime. The team’s fix involved integrating ProxySQL with Consul’s health checks, so proxy nodes automatically update their routing table when a primary switches.

Another lesson came from backup strategies. The authors initially used mysqldump for nightly backups, which took over 4 hours for a 500GB dataset. They switched to Percona XtraBackup, reducing backup time to 45 minutes. This aligns with industry best practices: incremental backups and physical backups are far superior for large-scale MySQL deployments.

The Future of Database Infrastructure

The Homescale project isn’t just a technical exercise. It highlights a growing trend: the democratization of database infrastructure. With tools like Vitess, ProxySQL, and Kubernetes, even small teams can build systems that rival PlanetScale. However, the complexity is real. The authors estimate that their home-lab setup required over 200 hours of configuration and debugging. For production use, they recommend starting with a managed service like PlanetScale itself, but for learning purposes, building from scratch is invaluable.

If you’re a developer curious about database internals, this article is a treasure trove. It shows that infrastructure isn’t just about picking the right tools — it’s about understanding how they interact under pressure. The Homescale team’s experience proves that even a small-scale replica of PlanetScale requires deep knowledge of networking, storage, and distributed systems.

Conclusion: Build or Buy?

In 2026, the choice between building your own database infrastructure and buying a managed service is still contentious. The Homescale project demonstrates that building is possible, but it’s not for the faint of heart. PlanetScale itself was born from the need to abstract away this complexity. Yet, for engineers who want to master the stack, recreating PlanetScale from scratch is a rite of passage.

The key takeaway? Whether you build or buy, understanding the infrastructure beneath your database is non-negotiable. The days of treating databases as black boxes are over. Dive into the Homescale source material, experiment with Vitess in your own lab, and you’ll emerge with a deeper appreciation for the systems that power modern applications. Source