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AI visibility report

AI visibility report for Neon in Databases & Data Infrastructure.

Outside the top three on 18 of the 25 prompts buyers actually ask.

PingCAP is cited on 6 of those losses.

25 prompts
6 platforms
Updated Jul 20, 2026 - refreshed weekly
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1percent
Presence Rate
Low presence

Still absent from 99.3% of tracked prompt responses

Top-3 citations across 150 prompt × platform pairs

+0.90
Sentiment
-1.00.0+1.0
Very positive
No clearrank

Peer Ranking

#1#15
No clear rankin Databases & Data Infrastructure

Key Metrics

Presence Rate0.7%
Share of Voice1.4%
Avg Position#1.0
Docs Presence0.7%
Blog Presence0.0%
Brand Mentions22.7%

Platform Breakdown

ChatGPT
4%1/25 prompts
Bing Copilot
0%0/25 prompts
Perplexity
0%0/25 prompts
Google AI Mode
0%0/25 prompts
Gemini Search
0%0/25 prompts
Grok
0%0/25 prompts

How to read this. Neon appears in 0.7% of tracked prompt responses. Presence is absolute coverage; share of voice is relative citation share; sentiment measures tone only when the brand appears.

Where Neon is losing

Prompts where competitors are visible and Neon is not.

These prompt-level losses are the first prompts to track and repair.

Where Neon is winning1

  • Which database platforms support branching so I can get a fresh isolated database copy per pull request for feature development?

    Avg # 1.0 · 1 platform

Where Neon is losing5

  • Which document databases handle schema evolution most smoothly — without requiring migration scripts for every change?

    Competitors on 4 platforms

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  • Which time-series databases maintain query performance best at 10 million events per second ingestion over long retention periods?

    Competitors on 4 platforms

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  • Which globally distributed SQL databases are worth evaluating for a latency-sensitive SaaS product compared to a traditional single-region setup?

    Competitors on 3 platforms

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  • Which distributed SQL platforms support migrating from a legacy relational database with minimal downtime for a production application?

    Competitors on 3 platforms

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  • Which columnar databases handle mixed OLAP and OLTP workloads well — when does it make sense to use one over a standard row-store?

    Competitors on 3 platforms

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Research dossierCapabilities, use cases, sources, reviews, pricing, and FAQ

Overview

Neon is a serverless Postgres platform built on a novel architecture that fully separates storage from compute, enabling databases to autoscale vertically, pause when idle, and resume in milliseconds. Founded in 2021 by Postgres committers Nikita Shamgunov, Heikki Linnakangas, and Stas Kelvich, Neon launched its open-source storage engine on GitHub and reached general availability in April 2024. The platform is notable for instant git-like database branching using copy-on-write storage, a fully usage-based pricing model, and a fleet management API suited for AI agents and developer platforms. In May 2025, Databricks acquired Neon for approximately $1 billion; the same technology now powers Databricks Lakebase. Neon reported over 40,000 databases created daily, with roughly 80% provisioned by AI agents rather than humans.

Neon is an open-source, developer-first serverless Postgres platform that re-architects PostgreSQL with a distributed, multi-tenant storage layer decoupled from compute. Its signature capabilities—instant database branching, automatic scale-to-zero, vertical autoscaling, and a REST/CLI API for fleet management—make it well-suited for modern application development workflows, AI agent backends, and developer platforms embedding Postgres for their users. Now a Databricks company, Neon's core technology also powers Databricks Lakebase.

Key Facts

Founded
2021
HQ
San Francisco, USA
Founders
Nikita Shamgunov, Heikki Linnakangas, Stas Kelvich
Funding
~$130.6M
ARR
~$25M
Status
Acquired by Databricks (May 2025)

Target users

Full-stack and backend developers building serverless or edge applicationsAI/ML engineers and agent platform builders requiring rapid database provisioningDeveloper platform and SaaS companies embedding Postgres for end usersDevOps and platform engineers managing large Postgres fleets via APIStartups seeking low-cost, scale-to-zero Postgres with no infrastructure overheadEngineering teams needing per-PR/branch isolated database environments in CI/CD

Key Capabilities10

  • Storage-compute separation enabling true serverless Postgres architecture
  • Instant git-like database branching with copy-on-write (no data duplication until divergence)
  • Automatic vertical autoscaling of CPU and RAM based on live workload
  • Scale-to-zero: databases pause when idle and resume in milliseconds
  • Point-in-time instant restore (PITR) up to 30 days on Scale plan
  • Built-in pgBouncer connection pooling supporting up to 10,000 client connections
  • Fleet-scale REST API for programmatic provisioning (databases in ~120ms)
  • Built-in Neon Auth for user authentication managed at the database layer
  • Read replicas with instant, autoscaling compute
  • Postgres extensions support including pgvector, pg_search, PostGIS, TimescaleDB

Key Use Cases7

  • Serverless and edge application backends requiring auto-scaling Postgres
  • AI agent platforms needing rapid, cost-effective fleet provisioning of isolated databases
  • Development and test environments with per-PR/branch isolated database copies
  • Multi-tenant SaaS with database-per-tenant isolation without overhead
  • Platform builders embedding managed Postgres for their end users via API
  • Applications with spiky or unpredictable traffic patterns (pay-per-use compute)
  • Large-scale Postgres fleet management for developer tool platforms

Neon customer outcomes

Retool

300,000+ databases managed by 1 engineer; 50% cost reduction vs. provisioned platform

Retool uses the Neon API to power RetoolDB, managing over 300,000 customer Postgres databases with a single engineer, automating virtually all database management tasks. Scale-to-zero eliminates idle compute costs across the fleet.

Vercel

99.99% uptime without over-provisioning

Vercel uses Neon's autoscaling to power Vercel Postgres, achieving 99.99% uptime without over-provisioning compute resources for its developer platform.

Recent Trend

Visibility-2.4 pts
Avg position-8.75
Sentiment+0.20

How AI describes Neon3

The best developer-focused databases for local development that closely mirror production are PostgreSQL-based solutions like Database Lab Engine, Neon, and Supabase Local Dev.

Which developer-focused databases offer the best local development experience that actually mirrors the production setup?

bing-copilot-searchDirect Neon mention
Fastest to spin up and connect for a Node.js SaaS backend: _Turso (libSQL) and Supabase_ are the quickest to get running, but Neon offers the best long-term developer workflow with Postgres branching and scale-to-zero.

What's the fastest serverless relational database to spin up and connect to a Node.js backend for a new SaaS app?

bing-copilot-searchDirect Neon mention
For a latency‑sensitive SaaS product, globally distributed SQL databases worth evaluating include Google Cloud Spanner, CockroachDB, YugabyteDB, and newer edge‑native SQL options like Turso (libSQL), Cloudflare D1, and Neon Postgres.

Which globally distributed SQL databases are worth evaluating for a latency-sensitive SaaS product compared to a traditional single-region setup?

bing-copilot-searchDirect Neon mention

Alternatives in Databases & Data Infrastructure6

Neon positions itself as the developer-first, open-source serverless Postgres platform built on true storage-compute separation—differentiating from managed Postgres offerings (AWS Aurora, Google AlloyDB) via genuine scale-to-zero economics, instant git-like database branching, and a fully usage-based pricing model.

  • Backed by Databricks since May 2025, Neon further differentiates by targeting AI-agent workloads that require millisecond database provisioning, fleet-scale API management, and cost-effective idle pausing—capabilities it argues neither hyperscaler nor competing Postgres-as-a-service vendors (e.g., Supabase, PlanetScale) match at the architectural level.
View category comparison hub

Reviews

Praised

  • Instant database branching speeds up development and testing
  • Easy setup and developer-friendly onboarding
  • Scale-to-zero eliminates idle compute costs
  • Strong Vercel and GitHub Actions integration
  • Open-source and Postgres-native—no lock-in
  • Responsive support team
  • Powerful fleet management via API

Criticized

  • Pricing model changes (shift from free to usage-based minimums)
  • Cold-start latency concerns for scale-to-zero in latency-sensitive production
  • Limited compute ceiling on lower-tier plans
  • Questions about roadmap autonomy post-Databricks acquisition

Community sentiment sourced from Product Hunt (5.0/5 across 66 reviews) and Hacker News discussions is broadly positive, with particular praise for database branching as a development-velocity multiplier and the simplicity of the serverless model. Users describe Neon as easy to set up, with strong reliability in practice. The main criticism noted across forums is around pricing model changes (a historical shift from fully free toward usage-based minimums) and occasional questions about cold-start latency for scale-to-zero databases in latency-sensitive production workloads. No verifiable aggregate scores were found on G2 or Gartner Peer Insights specifically for the neon.tech database product at time of research.

Pricing

Neon offers three self-serve tiers: Free ($0/month, no card required; 100 projects, 100 CU-hours per project, 0.5 GB storage, up to 2 CU compute, 6-hour PITR), Launch (usage-based, no monthly minimum; $0.106/CU-hour compute, $0.35/GB-month storage, $0.20/GB-month for PITR, up to 16 CU, 7-day PITR window), and Scale (usage-based, no monthly minimum; $0.222/CU-hour compute, $0.35/GB-month storage, up to 56 CU, 30-day PITR, SOC 2 report, HIPAA, private networking, 99.95% SLA). Additional branches are $1.50/branch-month beyond plan inclusions. An Enterprise tier and a custom Agent Plan (for platforms deploying thousands of databases) are available via sales. Early-stage startups can apply for up to $100K in credits through the Neon Startup Program.

Limitations

  • Neon is optimized for OLTP and general-purpose Postgres workloads; it is not designed for analytics-heavy or data warehouse use cases.
  • Autoscaling is capped at 16 CU (64 GB RAM) on Launch and 56 CU (224 GB RAM) on Scale plans; fixed compute sizes go up to 56 CU.
  • The Free plan limits compute to 2 CU (8 GB RAM) and 0.5 GB storage per project, with scale-to-zero enforced after 5 minutes.
  • Free plan PITR window is limited to 6 hours or 1 GB of data changes.
  • The platform runs on AWS infrastructure (multi-AZ storage), meaning teams requiring multi-cloud or on-premises deployment must use the open-source self-hosted path.
  • Post-Databricks acquisition, some users in community discussions have raised questions about long-term independent pricing and roadmap autonomy.

Frequently asked questions

Topic coverageCoverage by buyer topic

Topic Coverage

Capability0/5DevEx0/5Integrations &Ecosystem0/5Performance &Reliability0/5Setup & First Run1/5

Prompt-Level Results

Brand citedCompetitor citedNot cited
PromptBing CopilotPerplexityChatGPTGoogle AI ModeGemini SearchGrok
Capability0/5 cited (0%)

Which globally distributed SQL databases are worth evaluating for a latency-sensitive SaaS product compared to a traditional single-region setup?

What in-memory caching tools integrate best with persistent databases — and which are worth adding versus just optimizing primary database queries?

Which managed database platforms offer the best multi-region replication with automatic conflict resolution for write-write scenarios?

What are the best dedicated vector databases, and how do they compare to adding vector search extensions to an existing relational database?

Which columnar databases handle mixed OLAP and OLTP workloads well — when does it make sense to use one over a standard row-store?

Developer Experience0/5 cited (0%)

Which cloud-native database platforms handle connection pooling best for serverless workloads with unpredictable connection spikes?

Which ORMs and query builders offer the best TypeScript experience for a distributed SQL database?

Which time-series databases have the best query authoring and debugging experience for teams coming from relational databases?

Which document databases handle schema evolution most smoothly — without requiring migration scripts for every change?

Which developer-focused databases offer the best local development experience that actually mirrors the production setup?

Integrations & Ecosystem0/5 cited (0%)

Which developer-focused database platforms integrate best with IaC tools so database provisioning and config can be version-controlled?

What tools sync data from a primary operational database to an analytics warehouse for real-time reporting without heavy ETL infrastructure?

Which cloud database platforms support change data capture for streaming row-level changes to a message queue or event bus with low latency?

Which managed database platforms have the best ORM and query builder compatibility for JavaScript and Python ecosystems?

Which managed database platforms make multi-cloud portability practical — so moving between cloud providers isn't a nightmare?

Performance & Reliability0/5 cited (0%)

Which managed database services offer the best backup and point-in-time recovery for production applications handling financial transactions?

Which serverless database platforms maintain the best read/write throughput under sustained load with reliable autoscaling?

What tools and benchmarks help compare database platforms for high-concurrency transactional workloads before committing to one?

Which time-series databases maintain query performance best at 10 million events per second ingestion over long retention periods?

Which distributed SQL databases handle automatic failover most reliably when a node goes down — with the fastest recovery times?

Setup & First Run1/5 cited (20%)

What's the fastest serverless relational database to spin up and connect to a Node.js backend for a new SaaS app?

Which distributed SQL platforms support migrating from a legacy relational database with minimal downtime for a production application?

I'm evaluating managed cloud databases versus self-hosted options for a seed-stage product — what should I look at?

Which developer-focused database platforms handle schema migrations with CI/CD pipeline tooling out of the box?

Which database platforms support branching so I can get a fresh isolated database copy per pull request for feature development?

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Vertical Ranking

#BrandPres.SoVDocsBlogMent.PosSentiment
1PingCAP6.7%23.0%0.7%2.0%6.0%#4.7+0.28
2CockroachDB5.3%14.9%0.7%2.7%1.3%#3.0+0.33
3Supabase4.7%16.2%4.0%0.7%18.7%#2.8+0.71
4ClickHouse4.0%12.2%0.0%0.0%10.0%#3.9+0.38
5MongoDB2.7%6.8%2.0%0.0%27.3%#2.6+0.59
6QuestDB2.7%8.1%0.0%2.7%5.3%#3.0+0.67
7PlanetScale2.0%6.8%1.3%0.0%18.0%#4.6+0.82
8Timescale1.3%2.7%0.0%0.7%0.7%#7.0+0.68
9Xata1.3%2.7%0.0%1.3%2.7%#8.5+0.60
10Fauna0.7%1.4%0.0%0.0%1.3%#1.0+0.20
11Neon0.7%1.4%0.7%0.0%22.7%#1.0+0.90
12Redis0.7%1.4%0.0%0.0%12.7%#2.0+0.00
13SingleStore0.7%1.4%0.0%0.7%5.3%#3.0+0.20
14Turso0.7%1.4%0.7%0.0%6.7%#5.0+0.85
15Gel0.0%0.0%0.0%0.0%0.0%

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