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Neon

Open Source

About Neon

Neon provides a backend platform built on Lakebase Postgres for applications and agents. Neon is a complete backend platform that includes Authentication, Object Storage, Functions, and an AI Gateway alongside its database. The database component is a serverless Postgres database that scales and branches with an application. Neon is part of the Databricks Platform. The architecture decouples storage and compute. Pricing is usage-based, charging for resources actually used.

Products

  • Lakebase Postgres: Serverless Postgres database that scales and branches with an application.
  • Compute: Runs functions without timeouts close to the database.
  • Storage: S3-compatible object storage that branches with projects.
  • AI Gateway: Provides one API for frontier and open-source AI models, powered by Databricks.

Used for

  • Creating preview environments that include existing data via branching
  • Giving each idea its own isolated environment for agents to work in
  • Testing and rolling back changes safely
  • Offloading read-heavy queries using read replicas

Who it is for

  • Developers building applications on Postgres.
  • Early-stage startups.
  • Maintainers of open source projects.
  • App generation platforms.

From Neon's own website, read 2026-10-23. How we build listings.

How to evaluate Database Platforms

This is how the CIOPages Research Team evaluates this category. It is not an assessment of Neon. It comes from our Enterprise Database Platforms buyer guide.

25%
Data Model & Query Fit
Match of the engine to the workload: relational integrity and joins, document/JSON flexibility, key-value latency; transaction isolation levels and ACID guarantees; SQL standard coverage and dialect quirks; secondary indexes, full-text and vector (pgvector / Atlas Search) support; foreign keys and referential integrity where you need them
20%
Consistency, Scale & HA
Single-primary vs. multi-writer; synchronous vs. async replication and resulting RPO; read-replica and sharding story; horizontal write scale and global/multi-region behavior (strong vs. eventual consistency); failover time, achievable RTO, and how partitions are handled under load
20%
Operability & Managed-Service Experience
Quality of the managed offering (RDS/Aurora, Azure SQL, Cloud SQL/AlloyDB) vs. self-managed burden; in-place and major-version upgrade path; backup/PITR, observability, and connection pooling; autoscaling and serverless options; day-2 toil — vacuum/compaction, index bloat, rebalancing — and the depth of the DBA skills it demands
15%
Licensing & Portability
License class and its real constraints: OSI open source (PostgreSQL, MySQL, Valkey, Redis 8 AGPL) vs. source-available (MongoDB SSPL, CockroachDB enterprise/BSL) vs. proprietary (Oracle, SQL Server); cloud lock-in of proprietary engines (Aurora, Spanner, DynamoDB); wire-protocol and SQL-dialect compatibility that preserves an exit; audit exposure on proprietary metrics
12%
Security & Compliance
Encryption at rest and in transit, TLS enforcement, and key management (BYOK/HSM); row- and column-level security and fine-grained RBAC; field-level / queryable encryption for sensitive data; audit logging; data-residency controls and certifications (SOC 2, ISO 27001, HIPAA, PCI, FedRAMP) on the managed service
8%
Ecosystem & Talent
Driver and ORM maturity across your languages; migration and CDC tooling (logical replication, Debezium, DMS); breadth of extensions and integrations; size and hireability of the talent pool; quality of docs and the support path — first-party vendor vs. third-party (EDB, Percona, Crunchy) for open engines

CIOPages put this listing together from public sources. It’s information, not an endorsement. How we build listings. Work here? Claim this listing or .

Quick Facts

neon.tech Pricing page
CategoryData & Analytics
SubcategoryDatabase Platforms
PricingUsage-based with a free tier

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