AI Infrastructure🔴Developer

Neon

Name: Neon
Brand: Neon
Availability: InStock

Serverless Postgres with branching, autoscaling, and pgvector support for AI app retrieval workflows.

Starting atFree

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💡

In Plain English

Serverless Postgres with branching, autoscaling, and pgvector support for AI app retrieval workflows.

Overview

Neon is an AI Infrastructure tool with freemium pricing and paid plans from $19/month, offering serverless Postgres for teams that need managed PostgreSQL, autoscaling, database branching, scale-to-zero idle behavior, connection pooling, point-in-time recovery, and pgvector retrieval for AI applications without operating database servers. It is aimed at developers, platform teams, and AI product teams that want Postgres compatibility with a cloud-native operating model: storage is separated from compute, compute can pause when inactive, and teams can create isolated database branches for previews, pull requests, tests, agent workspaces, migration checks, and tenant-style environments. For AI workloads, Neon is most useful when the application benefits from keeping ordinary transactional records, document metadata, and vector embeddings inside PostgreSQL through pgvector rather than introducing a separate vector database early in the architecture. The database branching model is especially relevant for coding-agent and CI workflows because a branch can be created from an existing database state, receive its own connection string and compute, and be discarded after the experiment or pull request is complete. Pricing and limits should be read from Neon's current pricing page at https://neon.tech/pricing, which documents the Free plan, usage-based Launch and Scale plans, Free storage at 0.5 GB per project, Launch compute at $0.106 per CU-hour, Scale compute at $0.222 per CU-hour, Scale sizes up to 56 CU and 224 GB RAM, Free time travel/restores up to 6 hours, Launch up to 7 days, Scale up to 30 days, and pooled connections built on pgBouncer up to 10,000 connections. Neon's security page at https://neon.tech/security backs the compliance and security posture in this record, including SOC 2 Type II, GDPR, HIPAA, encryption in transit with TLS 1.2+, encryption at rest with AES-256, RBAC-oriented access controls, monitoring, audit logging, and trust-center documentation. MCP support is also documented by Neon at https://neon.tech/docs/ai/neon-mcp-server: the Neon MCP Server is described as an open-source tool for managing Neon projects, branches, databases, SQL queries, and schema changes through compatible MCP clients, with OAuth or API-key setup options. The managed Neon service is not a self-hosted Postgres distribution, but Neon does publish open-source developer tooling and exposes API, CLI, SDK, GitHub, ORM, framework, monitoring, and deployment integrations. The main trade-offs are cold-start latency when compute resumes from idle, cost modeling for high-utilization workloads, small Free-tier storage for realistic embedding datasets, extension compatibility differences versus self-managed PostgreSQL, and the process change required for teams adopting branch-based database development.

🦞

Using with OpenClaw

▼

Integrate Neon with OpenClaw through available APIs or create custom skills for specific workflows and automation tasks.

Use Case Example:

Extend OpenClaw's capabilities by connecting to Neon for specialized functionality and data processing.

Learn about OpenClaw →

🎨

Vibe Coding Friendly?

▼

Difficulty:beginner

No-Code Friendly ✨

Standard web service with documented APIs suitable for vibe coding approaches.

Learn about Vibe Coding →

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Editorial Review

Neon delivers genuinely innovative serverless PostgreSQL with database branching that transforms development workflows and scale-to-zero billing that eliminates costs for idle databases. Cold starts of 500-2000ms are the main trade-off. Best for teams wanting modern Postgres with Git-like workflows and pay-per-use economics.

Key Features

Database Branching+

Git-like branching using copy-on-write technology. New branches share base data and only consume storage for changes. Each branch gets its own connection string and compute.

Use Case:

Creating isolated database environments for each pull request so developers can test schema migrations against real data without affecting production.

Serverless Autoscaling + Scale to Zero+

Compute scales automatically based on demand from 0.25 to 56 CU (up to 224GB RAM on Scale tier). Idle databases pause automatically and resume within 500-2000ms on first connection.

Use Case:

Handling traffic spikes for a SaaS application during business hours while paying nothing overnight when no one is querying the database.

Point-in-Time Recovery+

Continuous backup with second-level granularity. Restore to any specific second within the retention period without traditional backup/restore processes. 6 hours Free, 7 days Launch, 30 days Scale.

Use Case:

Recovering from an accidental DELETE statement by restoring the database to the exact second before the query executed.

Built-in Connection Pooling+

pgBouncer-based connection pooling handles up to 10,000 concurrent connections efficiently, included on all plans at no extra cost.

Use Case:

Running a serverless application on Vercel where each function invocation opens a new connection — pooling prevents hitting PostgreSQL's connection limits.

GitHub Integration+

Automatically creates database branches for pull requests with schema migration previews. Branches are deleted when PRs are merged or closed.

Use Case:

Configuring CI/CD so every PR automatically gets a fresh database branch, runs migration tests, and reports results directly in the PR comments.

Neon Auth+

Built-in authentication based on Better Auth with one-click setup. Supports up to 60K MAUs on Free and 1M on Launch, eliminating the need for a separate auth service.

Use Case:

Adding user authentication to a new SaaS app without configuring a separate auth provider — enable Neon Auth and start building login flows immediately.

Pricing Plans

Free

$0/month

✓Serverless Postgres
✓Database branching
✓0.5GB project storage limit
✓6 hours point-in-time recovery
✓Neon Auth up to 60K monthly active users

Launch

$19/month

✓Paid serverless Postgres plan
✓Usage-based compute and storage
✓$0.106 per CU-hour
✓7 days point-in-time recovery
✓Neon Auth up to 1M monthly active users

Scale

$69/month

✓Higher-scale serverless Postgres plan
✓$0.222 per CU-hour
✓Compute scaling up to 56 CU
✓Up to 224GB RAM
✓30 days point-in-time recovery

Business/Enterprise

Custom pricing

✓Custom commercial terms
✓Enterprise-oriented support and controls
✓Managed Postgres infrastructure for larger teams
✓Suitable for production AI and data workloads
✓Backed by Databricks since 2025

See Full Pricing →Free vs Paid →Is it worth it? →

Ready to get started with Neon?

View Pricing Options →

Getting Started with Neon

1Create a Neon account and project at console.neon.tech — no credit card required
2Connect your application using the provided connection string (supports pooled and direct connections)
3Set up database branching for development and testing environments
4Configure autoscaling limits and auto-pause settings for your workload
5Integrate with GitHub for automatic PR-based database branches

Ready to start? Try Neon →

Best Use Cases

🎯

Building a RAG application where user records, document metadata, embeddings, and retrieval queries should live in one Postgres-compatible database instead of separate relational and vector systems.

⚡

Creating per-pull-request preview databases so frontend and backend developers can test schema migrations against production-like data before merging.

🔧

Running AI agent backends that need temporary scratch databases, isolated task state, or per-tenant environments without paying for always-on compute when agents are idle.

🚀

Deploying serverless applications on platforms such as Vercel where connection pooling is needed to avoid exhausting Postgres connection limits during traffic spikes.

💡

Operating a SaaS product with bursty usage patterns, such as heavy daytime traffic and low overnight activity, where scale-to-zero and autoscaling can reduce wasted spend.

🔄

Recovering from accidental data changes by using point-in-time recovery, such as restoring to the exact second before an erroneous DELETE or migration ran.

Integration Ecosystem

15 integrations

Neon works with these platforms and services:

🧠 LLM Providers

OpenAI

📊 Vector Databases

pgvector

☁️ Cloud Platforms

AWSVercelRailwaynetlifycloudflare

🗄️ Databases

PostgreSQL

🔐 Auth & Identity

Clerkbetter-auth

📈 Monitoring

Datadogopentelemetry

🔗 Other

GitHubprismadrizzle

View full Integration Matrix →

Limitations & What It Can't Do

We believe in transparent reviews. Here's what Neon doesn't handle well:

⚠Cold starts add 500-2000ms latency when databases resume from idle state, impacting latency-sensitive applications.
⚠Scale tier's per-CU-hour rate of $0.222 is 85% higher than Launch at $0.106, making cost modeling important for high-utilization workloads.
⚠Free tier storage is limited to 0.5GB per project, which may not be enough for development databases with realistic datasets or embeddings.
⚠Branching workflows require team education and process changes compared with a traditional shared staging database.
⚠Some PostgreSQL extensions are not supported in the serverless environment due to storage and compute separation.

Pros & Cons

✓ Pros

✓Scale-to-zero compute can reduce idle database cost to $0 for workloads that only run when queried, which is useful for preview environments, prototypes, and bursty AI agents.
✓Database branching uses copy-on-write behavior, so teams can create isolated branches from production data without paying for a full duplicate of the base database immediately.
✓pgvector support with HNSW lets many RAG applications keep embeddings, metadata, and transactional data inside Postgres instead of adding a separate vector database.
✓Autoscaling from 0.25 to 56 CU, with up to 224GB RAM on the Scale tier, gives teams a path from small development databases to much larger production workloads.
✓Built-in pgBouncer-based pooling supports up to 10,000 concurrent connections, which is valuable for Vercel-style serverless applications with many short-lived processes.
✓Databricks acquired Neon in 2025, which gives the platform stronger backing in the data and AI infrastructure market than most independent Postgres startups.

✗ Cons

✗Cold starts of 500-2000ms can be noticeable on latency-sensitive production request paths unless auto-pause is disabled or carefully configured.
✗The Free tier's 0.5GB project storage limit is small for realistic development databases, embedding stores, or test environments with production-like data.
✗Scale tier compute at $0.222 per CU-hour is substantially higher than the Launch tier's $0.106 per CU-hour, so high-utilization 24/7 workloads can become expensive.
✗Teams must adapt their development process to branch-based database workflows; it is powerful, but different from a traditional shared staging database.
✗Some PostgreSQL extensions are not supported in the serverless environment because Neon's storage and compute architecture differs from a conventional self-managed Postgres instance.

Frequently Asked Questions

Is Neon a good database for AI and RAG applications?+

Yes, Neon is a strong fit for many RAG applications because it supports Postgres plus pgvector, allowing teams to store relational records, metadata, and embeddings in one system. The provided data notes pgvector with HNSW, which is important for approximate nearest-neighbor search over embeddings.

How does Neon's database branching work?+

Neon database branching uses copy-on-write behavior, so a new branch starts by sharing the base data and only consumes additional storage for changes made after the branch is created. Each branch gets its own connection string and compute, which makes it practical to create isolated databases for pull request workflows.

What should teams know about Neon cold starts?+

Neon can pause idle compute and resume it when the next query arrives, which is how it achieves a very low idle-cost posture. The provided data lists cold starts in the 500-2000ms range, so the first request after an idle period may be slower than normal.

How does Neon pricing compare with traditional managed Postgres?+

Neon's pricing starts with a Free tier and paid plans from $19/month for Launch and $69/month for Scale, according to the provided tool data. Its main pricing advantage appears when databases are idle or bursty, because compute can scale to zero instead of running continuously.

Can Neon replace Supabase or a dedicated vector database?+

Neon can replace a dedicated vector database for many early and mid-stage RAG applications when pgvector performance and Postgres-native workflows are sufficient. It is not a full Supabase replacement if a team wants an all-in-one app platform with storage, generated APIs, and broader backend product features.

🔒 Security & Compliance

🛡️ SOC2 Compliant

✅

SOC2

Yes

✅

GDPR

Yes

✅

HIPAA

Yes

✅

SSO

Yes

❌

Self-Hosted

❌

On-Prem

✅

RBAC

Yes

✅

Audit Log

Yes

✅

API Key Auth

Yes

✅

Open Source

Yes

✅

Encryption at Rest

Yes

✅

Encryption in Transit

Yes

Data Retention: configurable

Data Residency: US, EU, ASIA

📋 Privacy Policy →🛡️ Security Page →

🦞

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What's New in 2026

In 2026, Neon enhanced agent capabilities with improved cold start performance, better branching workflows, enhanced monitoring tools, and new features for optimizing serverless database costs.

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User Reviews

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Quick Info

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More about Neon

Pricing Review Alternatives Free vs Paid Pros & Cons Worth It?Tutorial

Overview

Editorial Review

Key Features

Database Branching+

Git-like branching using copy-on-write technology. New branches share base data and only consume storage for changes. Each branch gets its own connection string and compute.

Use Case:

Creating isolated database environments for each pull request so developers can test schema migrations against real data without affecting production.

Serverless Autoscaling + Scale to Zero+

Compute scales automatically based on demand from 0.25 to 56 CU (up to 224GB RAM on Scale tier). Idle databases pause automatically and resume within 500-2000ms on first connection.

Use Case:

Handling traffic spikes for a SaaS application during business hours while paying nothing overnight when no one is querying the database.

Point-in-Time Recovery+

Continuous backup with second-level granularity. Restore to any specific second within the retention period without traditional backup/restore processes. 6 hours Free, 7 days Launch, 30 days Scale.

Use Case:

Recovering from an accidental DELETE statement by restoring the database to the exact second before the query executed.

Built-in Connection Pooling+

pgBouncer-based connection pooling handles up to 10,000 concurrent connections efficiently, included on all plans at no extra cost.

Use Case:

Running a serverless application on Vercel where each function invocation opens a new connection — pooling prevents hitting PostgreSQL's connection limits.

GitHub Integration+

Automatically creates database branches for pull requests with schema migration previews. Branches are deleted when PRs are merged or closed.

Use Case:

Configuring CI/CD so every PR automatically gets a fresh database branch, runs migration tests, and reports results directly in the PR comments.

Neon Auth+

Built-in authentication based on Better Auth with one-click setup. Supports up to 60K MAUs on Free and 1M on Launch, eliminating the need for a separate auth service.

Use Case:

Adding user authentication to a new SaaS app without configuring a separate auth provider — enable Neon Auth and start building login flows immediately.

Pricing Plans

Free

$0/month

✓Serverless Postgres
✓Database branching
✓0.5GB project storage limit
✓6 hours point-in-time recovery
✓Neon Auth up to 60K monthly active users

Launch

$19/month

✓Paid serverless Postgres plan
✓Usage-based compute and storage
✓$0.106 per CU-hour
✓7 days point-in-time recovery
✓Neon Auth up to 1M monthly active users

Scale

$69/month

✓Higher-scale serverless Postgres plan
✓$0.222 per CU-hour
✓Compute scaling up to 56 CU
✓Up to 224GB RAM
✓30 days point-in-time recovery

Business/Enterprise

Custom pricing

✓Custom commercial terms
✓Enterprise-oriented support and controls
✓Managed Postgres infrastructure for larger teams
✓Suitable for production AI and data workloads
✓Backed by Databricks since 2025

Getting Started with Neon

1Create a Neon account and project at console.neon.tech — no credit card required

2Connect your application using the provided connection string (supports pooled and direct connections)

3Set up database branching for development and testing environments

4Configure autoscaling limits and auto-pause settings for your workload

5Integrate with GitHub for automatic PR-based database branches

Best Use Cases

🎯

Building a RAG application where user records, document metadata, embeddings, and retrieval queries should live in one Postgres-compatible database instead of separate relational and vector systems.

⚡

Creating per-pull-request preview databases so frontend and backend developers can test schema migrations against production-like data before merging.

🔧

Running AI agent backends that need temporary scratch databases, isolated task state, or per-tenant environments without paying for always-on compute when agents are idle.

🚀

Deploying serverless applications on platforms such as Vercel where connection pooling is needed to avoid exhausting Postgres connection limits during traffic spikes.

💡

Operating a SaaS product with bursty usage patterns, such as heavy daytime traffic and low overnight activity, where scale-to-zero and autoscaling can reduce wasted spend.

🔄

Recovering from accidental data changes by using point-in-time recovery, such as restoring to the exact second before an erroneous DELETE or migration ran.

Limitations & What It Can't Do

We believe in transparent reviews. Here's what Neon doesn't handle well:

⚠Cold starts add 500-2000ms latency when databases resume from idle state, impacting latency-sensitive applications.

⚠Scale tier's per-CU-hour rate of $0.222 is 85% higher than Launch at $0.106, making cost modeling important for high-utilization workloads.

⚠Free tier storage is limited to 0.5GB per project, which may not be enough for development databases with realistic datasets or embeddings.

⚠Branching workflows require team education and process changes compared with a traditional shared staging database.

⚠Some PostgreSQL extensions are not supported in the serverless environment due to storage and compute separation.

Pros & Cons

✓ Pros

✓Scale-to-zero compute can reduce idle database cost to $0 for workloads that only run when queried, which is useful for preview environments, prototypes, and bursty AI agents.
✓Database branching uses copy-on-write behavior, so teams can create isolated branches from production data without paying for a full duplicate of the base database immediately.
✓pgvector support with HNSW lets many RAG applications keep embeddings, metadata, and transactional data inside Postgres instead of adding a separate vector database.
✓Autoscaling from 0.25 to 56 CU, with up to 224GB RAM on the Scale tier, gives teams a path from small development databases to much larger production workloads.
✓Built-in pgBouncer-based pooling supports up to 10,000 concurrent connections, which is valuable for Vercel-style serverless applications with many short-lived processes.
✓Databricks acquired Neon in 2025, which gives the platform stronger backing in the data and AI infrastructure market than most independent Postgres startups.

✗ Cons

✗Cold starts of 500-2000ms can be noticeable on latency-sensitive production request paths unless auto-pause is disabled or carefully configured.
✗The Free tier's 0.5GB project storage limit is small for realistic development databases, embedding stores, or test environments with production-like data.
✗Scale tier compute at $0.222 per CU-hour is substantially higher than the Launch tier's $0.106 per CU-hour, so high-utilization 24/7 workloads can become expensive.
✗Teams must adapt their development process to branch-based database workflows; it is powerful, but different from a traditional shared staging database.
✗Some PostgreSQL extensions are not supported in the serverless environment because Neon's storage and compute architecture differs from a conventional self-managed Postgres instance.