PlanetScale vs Neon: Which Cloud Database Fits Your App?
PlanetScale bets on provisioned performance and Vitess-scale sharding; Neon bets on serverless Postgres that autoscales and branches. Here's how they actually differ.
PlanetScale and Neon both call themselves modern cloud database platforms, but they solve the problem from opposite ends. PlanetScale sells provisioned, always-on clusters tuned for raw performance and horizontal scale — it grew out of Vitess, the sharding system built at YouTube, and now also offers Postgres and local-NVMe "Metal" clusters. Neon sells serverless Postgres: storage and compute are separated so the database can autoscale, pause when idle, and spin up instant branches.
The practical question isn't which is "better" in the abstract — it's whether your workload wants a scale-to-zero serverless Postgres you barely think about, or a provisioned engine you can push to extreme throughput and shard across many nodes. This comparison breaks down engines, pricing, developer workflow, and scaling so you can match the tool to the job. Confirm current pricing on each vendor's site before committing, since both change plans often.
At a glance
Choose PlanetScale for MySQL, horizontal sharding, or provisioned high-performance clusters (Metal NVMe) with predictable billing. Choose Neon for serverless Postgres with a free tier, scale-to-zero, instant branching, and AI-agent-friendly tooling. PlanetScale optimizes the performance ceiling; Neon optimizes idle cost and developer workflow.
Head to head
Key differences side by side; the stronger option is tinted green.
| Feature | PlanetScale | Neon |
|---|---|---|
| Pricing model | Provisioned, resource-based (from ~$5/mo, no free tier) | Serverless, usage-based (free tier + paid plans) |
| Free plan | None (removed in 2024) | Yes, free plan available |
| Scale to zero | No — clusters are always-on | Yes — idle compute pauses |
| Database engines | MySQL (Vitess) + Postgres | Postgres only |
| Horizontal sharding | Yes, via Vitess (petabyte scale) | No native sharding |
| Peak performance option | Metal: local NVMe, marketed as unlimited IOPS | Autoscaling compute |
| Branching for dev/test | Yes (schema branching, deploy requests) | Yes (instant copy-on-write branches) |
| AI-agent / serverless tooling | MCP support | MCP, Data API, built-in Auth |
| Company backing | Independent company | Databricks company |
Feature matrix
| Feature | PlanetScale | Neon |
|---|---|---|
| Free tierPlanetScale removed its Hobby free tier in 2024. | ✗ | ✓ |
| Serverless scale-to-zero | ✗ | ✓ |
| PostgreSQL supportPlanetScale Postgres is newer; Neon is Postgres-native. | ✓ | ✓ |
| MySQL supportVia Vitess. | ✓ | ✗ |
| Horizontal shardingPlanetScale uses Vitess for shard-based scale-out. | ✓ | ✗ |
| Database branchingNeon branches are instant, copy-on-write. | ✓ | ✓ |
| Autoscaling computePlanetScale autoscales storage/IOPS; compute is resized on provisioned instances. | △ | ✓ |
| Local NVMe (high IOPS)PlanetScale Metal tier. | ✓ | ✗ |
| Built-in authenticationNeon Auth stores users/sessions in Postgres. | ✗ | ✓ |
| Read replicas | ✓ | ✓ |
| Point-in-time / instant restore | ✓ | ✓ |
| REST Data API | ✗ | ✓ |
| MCP for AI agents | ✓ | ✓ |
| Bring your own cloudPlanetScale Managed deploys in your AWS/GCP; Neon offers this on enterprise. | ✓ | △ |
✓ full · △ partial/paid · ✗ not supported
Pricing
Confirm current pricing on each vendor's site.
- Single primary node
- Development and low-traffic production
- Resource-based billing (upsize/downsize as needed)
- 100 GB egress included
- 1 primary + 2 replicas across 3 AZs
- 99.99% SLA
- Autoscaling storage and configurable IOPS
- MySQL/Vitess or Postgres
- Local NVMe storage
- Marketed as unlimited IOPS, ultra-low latency
- Highest-performance tier
- Available for Postgres and Vitess
- Serverless Postgres with scale-to-zero
- Database branching
- Good for hobby projects and prototypes
- Autoscaling within free limits
- Billed on compute time + storage
- Higher limits, more branches and projects
- Instant read replicas and restore
- Built-in Auth and Data API
- Custom terms and support
- Compliance and security options
- For large or regulated workloads
- Contact sales
Pros & cons
- Vitess horizontal sharding proven at very large scale (Slack, GitHub, HubSpot)
- Metal tier offers local NVMe and high IOPS for performance-sensitive workloads
- Supports both MySQL and Postgres
- Reviewed, non-blocking schema changes via deploy requests
- High-availability clusters with a 99.99% SLA and predictable, provisioned billing
- No free tier — paid from around $5/month
- No serverless scale-to-zero; you pay for always-on provisioned capacity
- Vitess/sharding can be more than a small app needs
- Its Postgres offering is newer than Neon's
- Free plan plus usage-based billing that rewards idle/spiky workloads
- Scale-to-zero serverless compute separated from storage
- Instant copy-on-write branching for CI, previews, and testing
- Native Postgres with built-in Auth, Data API, and strong AI-agent tooling
- Backed by Databricks
- Postgres only — no MySQL
- No horizontal sharding like Vitess for extreme scale
- Autoscaling and cold starts can introduce latency variability
- Usage-based costs can be harder to predict at high, steady load
Two different answers to the same problem
PlanetScale's pitch is performance and scale on provisioned hardware. Its clusters run one primary plus a minimum of two replicas across three availability zones, and its Metal tier uses locally-attached NVMe drives that the company markets as delivering unlimited IOPS and very low latency. For workloads that outgrow a single machine, PlanetScale's Vitess engine adds horizontal sharding — distributing data across many nodes behind a single connection.
Neon's pitch is serverless Postgres. It separates storage from compute so the compute layer can scale up and down with traffic, and scale to zero when nothing is querying — you pay for what you use rather than a fixed instance size. That architecture also enables copy-on-write branching, instant point-in-time restore, and autoscaling read replicas. Neon is now a Databricks company, which points it further toward analytics and AI workloads.
So the split is real: PlanetScale optimizes the ceiling (how far and fast you can push a database), Neon optimizes the floor and the workflow (how little you pay when idle, and how fast you can spin up throwaway copies).
Database engines and architecture
PlanetScale started as managed Vitess — a MySQL-compatible system that scales horizontally through explicit sharding. Queries route through a component called VTGate, which fans out to sharded primaries and their replicas, an approach that powers very large properties like Slack, GitHub, and HubSpot. PlanetScale has since added PlanetScale Postgres, a fully-managed PostgreSQL-compatible option, so you can pick MySQL/Vitess for hyperscale sharding or Postgres for a more conventional relational setup.
Neon is Postgres and only Postgres. Instead of sharding horizontally, it decouples the storage engine from the compute nodes, keeping data in a storage layer that branches cheaply and lets compute autoscale independently. Neon adds developer-facing pieces on top: connection pooling, a REST Data API, built-in authentication, and read replicas that spin up instantly.
If your team already runs MySQL, PlanetScale is the natural fit. If you're committed to Postgres and want the serverless operational model, Neon is purpose-built for it — and PlanetScale Postgres is the newer entrant of the two Postgres offerings.
Pricing and the free-tier question
This is where the platforms diverge most visibly. PlanetScale removed its free "Hobby" tier in 2024, and today its Base plan is paid and resource-based: you provision instance size and pay for it. According to PlanetScale's pricing page, Postgres single-node clusters start at about $5/month for development and low-traffic use, a high-availability PS-5 configuration (1 primary + 2 replicas) starts around $15/month, and Metal clusters with local NVMe start near $50/month. Egress includes 100 GB, with additional bandwidth billed per GB.
Neon keeps a free plan and layers usage-based paid tiers (commonly Launch, Scale, and Business) on top, billing primarily on compute time and storage, plus an Enterprise option with custom terms. Because compute can scale to zero, a lightly-used project can cost very little, while a busy one is billed for what it consumes.
The trade-off: Neon's usage-based model rewards spiky or idle workloads and gives you a free starting point, while PlanetScale's provisioned model gives predictable monthly costs and no surprise usage spikes — but no free tier to start on. Treat all figures here as tiers, not quotes, and verify the current numbers on planetscale.com/pricing and neon.com/pricing.
Developer experience and workflows
Both platforms treat the database like code. PlanetScale offers schema branching, deploy requests (a pull-request-style review flow for schema changes), and non-blocking online schema changes — features that come from its Vitess heritage and are aimed at teams shipping migrations without downtime. Query insights help you find slow statements.
Neon's branching is a headline feature: branches are copy-on-write, so you can fork a full production-like database in seconds for a CI run, a preview environment, or a risky migration, then throw it away. Combined with scale-to-zero, this makes ephemeral per-pull-request databases cheap.
On the AI side, both expose a Model Context Protocol (MCP) integration so coding agents can operate the database. Neon leans harder into the agent and serverless story — its Data API, built-in Auth, and one-command setup (npx neonctl init) are designed for apps and agents to provision Postgres programmatically. If instant, disposable branches for testing and preview deploys are central to your workflow, Neon has an edge; if reviewed, gated schema changes on a provisioned cluster matter more, PlanetScale's deploy requests are compelling.
Scaling and performance
The scaling models are genuinely different. PlanetScale scales two ways: vertically, by choosing larger provisioned instances and Metal NVMe nodes for high IOPS, and horizontally, by sharding with Vitess. Vitess was designed to run enormous MySQL deployments — the kind measured in petabytes across tens of thousands of nodes — so it targets applications hitting the limits of a single machine. PlanetScale advertises a 99.99% SLA on its high-availability clusters.
Neon scales compute automatically with load and offers instant read replicas to spread read traffic, plus multi-terabyte storage with instant restore. It scales the compute layer up and down rather than sharding data across nodes, which fits variable web-app traffic well. The flip side of serverless is variability: a database that has scaled to zero has to wake up, and autoscaling introduces some latency variance that a permanently-provisioned PlanetScale instance avoids.
For extreme, sustained throughput or sharded MySQL at massive scale, PlanetScale's model is the more direct answer. For applications with uneven traffic that want the database to track demand without manual capacity planning, Neon's autoscaling is the more convenient one.
Which one fits your project
Reach for PlanetScale if you run MySQL, expect to shard, need consistently high IOPS on provisioned hardware, or want reviewed schema-change workflows with a firm SLA. Reach for Neon if you're building on Postgres, want a free starting point and usage-based billing, rely on instant branching for dev/test/preview environments, or are building AI-agent and serverless apps that provision databases on the fly.
Many teams also weigh operational philosophy: PlanetScale asks you to think about instance sizing and pays you back in predictable performance; Neon asks you to think in terms of usage and pays you back in elasticity and low idle cost. Neither is universally correct — the right pick depends on your engine, traffic shape, and how much you value scale-to-zero versus provisioned headroom.
These platforms aren't really competing for the same slot. PlanetScale is the stronger choice when scale and performance drive the decision: MySQL teams, workloads that need Vitess sharding, and applications that benefit from provisioned NVMe throughput and a firm SLA. Its lack of a free tier and its always-on billing are the cost of that predictability.
Neon is the stronger choice for Postgres-first teams who want serverless economics — a free starting point, scale-to-zero, and instant branching that makes ephemeral test and preview databases cheap. Its serverless model trades some latency predictability for elasticity, and it won't shard the way Vitess does.
Decide by engine and traffic shape first: pick PlanetScale if you're on MySQL or chasing a high, steady performance ceiling; pick Neon if you're on Postgres and value elasticity, low idle cost, and agent-friendly workflows. Both offer branching, replicas, and restore, so the deciding factors are usually pricing model and how far you need to scale. Verify current plans and limits on each vendor's site before you build.
FAQ
Does PlanetScale still have a free tier?
No. PlanetScale removed its free Hobby tier in 2024. Its Base plan is now paid and resource-based, starting at roughly $5/month for a single-node Postgres database. Neon, by contrast, still offers a free plan, so it's the option to start with at no cost.
Does Neon support MySQL, or only Postgres?
Neon is Postgres only. If you need MySQL, PlanetScale is the fit — it offers MySQL through Vitess (with horizontal sharding) as well as a newer PostgreSQL-compatible option.
Can I migrate between PlanetScale and Neon?
If you're using PlanetScale Postgres, standard Postgres tooling like pg_dump and pg_restore makes moving to or from Neon straightforward. Moving from PlanetScale's MySQL/Vitess to Neon's Postgres is a cross-engine migration that requires schema and data conversion, so plan for more work there.
Which is better for AI agents and serverless apps?
Both expose a Model Context Protocol (MCP) integration for coding agents. Neon leans further into this use case with scale-to-zero compute, one-command provisioning, a REST Data API, and built-in Auth, which suits agents that create and tear down databases programmatically. PlanetScale is the better pick when the agent-backed app needs sharding or provisioned high performance.