Neon
The serverless Postgres with a generous free tier, autoscaling, branching, and bottomless storage for modern applications.
Overview
Neon is a serverless PostgreSQL offering that redefines how developers interact with their databases. It separates compute and storage, allowing each to scale independently, which is crucial for modern, dynamic applications. This architecture enables features like instant branching, where developers can create isolated copies of their database for development, testing, or feature branches, much like using Git for code. The platform also boasts autoscaling capabilities, automatically adjusting compute resources based on demand, and bottomless storage, eliminating the need for manual capacity planning. With a focus on developer experience, Neon provides a robust API, connection pooling for high concurrency, and features tailored for AI applications, making it a powerful choice for building scalable and resilient data-driven products.
Pricing
Free
- 20 projects
- 100 CU-hours per project
- 0.5 GB per project
- Sizes to 2 CU (2 vCPU, 8 GB RAM)
- Autoscaling
- Read replicas
- Built-in high availability
Launch
- 100 projects
- $0.14 per CU-hour compute
- $0.35 per GB-month storage
- Sizes up to 16 CU (16 vCPU, 64 GB RAM)
- All features in Free
- 7-day time travel/PITR
- 3-day monitoring retention
Pros & Cons
Pros
- Serverless architecture provides automatic scaling and cost efficiency for variable workloads.
- Database branching enables modern development workflows, similar to Git, for isolated environments.
- Bottomless storage ensures data growth without manual intervention or capacity planning.
- Instant restore capabilities allow quick recovery from data issues or for testing purposes.
- Connection pooling handles a large number of connections, suitable for serverless functions.
- Offers a generous free tier, making it accessible for startups and individual developers.
Cons
- Being a managed service, it might offer less granular control over the underlying infrastructure compared to self-hosting.
- Performance might be subject to the cloud provider's infrastructure and network latency.
- Reliance on a specific vendor for database management could lead to vendor lock-in.
- Advanced features might require a learning curve for developers new to serverless Postgres concepts.
Use Cases
Reviews & Ratings
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Best For
- Serverless applications requiring an autoscale database backend.
- Multi-TB databases needing instant scaling and restore capabilities.
- Database-per-tenant architectures for data isolation without overhead.
- Platforms offering Postgres to their users.
- Development and testing environments requiring production-like data.
- Building full-stack AI agents with integrated database support.
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