6 posts tagged with "mysql"

DigitalOcean Managed Databases is a popular starting point for teams that want hosted PostgreSQL, MySQL, MongoDB, or Valkey without managing infrastructure. It does the basics well: provisioning, automated backups, and TLS. But as your data platform matures, the limitations become clear. Four engines, minimal monitoring, no AI-oriented features, no pipeline templates, and no way to export metrics to your own observability stack. FoundryDB offers seven engines, built-in AI presets, predictive autoscaling, database forking, and seven metrics export destinations, all on European infrastructure.

PlanetScale removed its free tier in April 2024 and raised prices across the board, pushing many teams to re-evaluate their MySQL hosting. Beyond pricing, PlanetScale runs on Vitess, a sharding proxy that sits between your application and MySQL. While Vitess handles horizontal scaling well, it introduces compatibility quirks that can surprise you: no foreign key enforcement, limited support for certain joins, and behavior differences from native MySQL. If you want a standard MySQL experience with native replication, foreign keys, and no proxy layer, FoundryDB is a direct path forward.

Most database dashboards give you a SQL editor and wish you luck. That works fine when you remember the exact name of the pg_stat_user_tables view or the difference between information_schema.TABLES in MySQL versus PostgreSQL. For everyone else, there is the AI Query Console.

FoundryDB's AI Query Console lets you type a question in plain English, translates it to a database-native SQL query using Claude, and executes it against your running service. The entire flow is read-only by design. You cannot accidentally drop a table by asking a question.

Every managed database service on FoundryDB gets automated backups from the moment it starts running. There is nothing to configure, no S3 bucket to provision, and no cron job to maintain. Backups run daily, are encrypted before they leave the server, and are stored in object storage across a separate availability zone.

But automated daily backups are only half the story. For PostgreSQL, MySQL, and MongoDB, FoundryDB continuously archives write-ahead logs (WAL), binary logs (binlog), or oplogs to enable point-in-time recovery (PITR). This means you can restore to any specific second within a 7-day window, not just to the last daily snapshot.

This post covers how backups work across all engines, how to trigger and restore them, and how to use PITR to recover from the kind of mistakes that daily snapshots cannot fix.

Every database connection costs memory. PostgreSQL forks a backend process per connection (roughly 5-10 MB each), and MySQL allocates per-thread buffers that scale with your buffer configuration. At 200 concurrent connections, the overhead is manageable. At 2,000, you are spending gigabytes of RAM on connection state instead of query execution.

Connection pooling sits between your application and the database, multiplexing many client connections over a small number of backend connections. FoundryDB provides PgBouncer for PostgreSQL and ProxySQL for MySQL, both managed through the API with no manual SSH or config file editing required.

If you run a modern application stack, you probably use at least three different database engines. PostgreSQL for your application data. MongoDB or another document store for unstructured content. Valkey (or Redis) for caching and session storage. Kafka for event streaming. Maybe MySQL for a legacy service that nobody wants to migrate.

Each engine runs on a different managed provider. Each provider has its own dashboard, its own CLI, its own billing, its own alerting system, its own way of handling backups, its own access control model. You pay five bills, manage five sets of credentials, and context-switch between five different interfaces when something goes wrong at 2 AM.

We built FoundryDB to solve this problem: one platform for all your database engines, with a single API, a single dashboard, and a single bill.