Managed Vitess/MySQL and Postgres with branching, sharding, and Metal NVMe clusters
PlanetScale documents a relational database platform at planetscale.com/docs supporting both Vitess-backed MySQL clusters and PostgreSQL-compatible databases with branching, deploy requests, query insights, and optional horizontal sharding for large Vitess workloads. Official docs describe locally attached NVMe "Metal" storage for high IOPS, multi-AZ primaries with replicas, the `@planetscale/database` serverless HTTP driver for edge and serverless hosts that block outbound TCP, and standard MySQL connections via dashboard credentials or the `pscale connect` proxy CLI. PlanetScale also documents vector support alongside relational data for both MySQL and Postgres engines per the documentation index at planetscale.com/docs/llms.txt.
Use cases
- Scaling MySQL-backed SaaS with non-blocking schema changes and production branches
- Connecting Vercel/Cloudflare Workers-style hosts via the serverless driver instead of TCP MySQL clients
- Running Postgres with PlanetScale branching for preview environments tied to pull requests
- Pairing relational tables with vector fields for RAG catalogs without a separate vector DB
- Evaluating Metal NVMe clusters when Aurora/Cloud SQL latency becomes a bottleneck
Key features
- Managed Vitess/MySQL and Postgres clusters with branching and deploy-request workflows per PlanetScale docs
- Query insights and schema recommendations surfaced in the dashboard and API
- HTTP serverless driver (`@planetscale/database`) for environments without arbitrary TCP egress
- `pscale` CLI for connect proxies, branch management, and automation via GitHub Actions
- Optional Vitess horizontal sharding and vector columns documented for MySQL and Postgres engines
Who Is It For?
- Backend engineers operating high-traffic MySQL or Postgres applications
- Platform teams standardizing database branching across microservices
- Serverless developers blocked from traditional MySQL TCP drivers
Frequently Asked Questions
- Does PlanetScale support only MySQL?
- No—PlanetScale docs cover both Vitess/MySQL clusters and PostgreSQL-compatible databases; pick the engine that matches your workload.
- How do serverless apps connect?
- Use the PlanetScale serverless driver documented at planetscale.com/docs/vitess/tutorials/planetscale-serverless-driver for HTTP-based queries when TCP is restricted.
- Can agents access PlanetScale metadata?
- PlanetScale documents a hosted MCP server at planetscale.com/docs/connect/mcp for OAuth-scoped schema and Insights access from Cursor or Claude.
Related
Related
3 Indexed items
Supabase
Supabase documents an open-source Postgres development platform at supabase.com/docs providing a hosted backend with database, authentication, storage, Edge Functions, realtime subscriptions, and vector search for web and mobile apps. Client libraries and REST/GraphQL APIs let teams provision projects via the dashboard or CLI, manage Row Level Security policies, and integrate AI workflows through pgvector-backed tables and partner marketplace tools. Supabase positions the stack as a Firebase alternative built on standard Postgres, with local development via the Supabase CLI and typed client SDKs for JavaScript, Flutter, Swift, and other frameworks per the documentation index.
AssemblyAI
AssemblyAI documents Voice AI APIs at assemblyai.com/docs where developers transcribe and analyze audio via REST at `https://api.assemblyai.com` and real-time WebSockets at `wss://streaming.assemblyai.com` (EU pre-recorded host `api.eu.assemblyai.com` per cloud residency docs). Pre-recorded transcription requires an explicit `speech_models` array on every `POST /v2/transcript` request—docs recommend `universal-3-pro` with `universal-2` fallback for 99-language coverage. The platform also publishes a Voice Agent API for speech-to-speech agents, Speech Understanding features (diarization, sentiment, summarization), Guardrails, and an LLM Gateway to run frontier models on transcripts.
NVIDIA NIM
NVIDIA NIM documents performance-optimized inference microservices at docs.api.nvidia.com/nim and docs.nvidia.com/nim that expose industry-standard APIs (OpenAI-compatible `/v1/chat/completions`, `/v1/completions`, `/v1/responses`, Anthropic-compatible `/v1/messages`) from containerized models backed by TensorRT-LLM, vLLM, or SGLang per deployment. Teams can self-host GPU-accelerated models on cloud, data center, or RTX workstations, or prototype via NVIDIA-hosted NIM API endpoints through the Developer Program. Management endpoints such as `/v1/health/ready` and `/v1/metrics` support readiness probes and Prometheus metrics on self-hosted containers per the LLM API reference.