Postgres consulting: complex problems, clear solutions
We love startups. And we're extremely passionate about Postgres, an awesome DBMS.
Over 5 years, we've helped dozens of startups master their PostgreSQL challenges. Two of them, GitLab (NASDAQ:GTLB) and Chewy (NYSE: CHWY), went through successful IPOs with our team helping them ensure Postgres clusters stayed reliable and performant as they scaled to many thousands of engineers and $10-20B market caps. We know how to help teams handle database growth with confidence.
Reach out to the Postgres.AI team to get help with Postgres now: [email protected].
When to engage​
You need us if you're a fast-growing startup on PostgreSQL (whether it's managed services like RDS or Supabase, or self-managed with or without Kubernetes), seeing good traction, but hitting database bottlenecks that your team or managed service provider struggles to solve efficiently. We step in to resolve these challenges and set you up for continued growth.
Our approach​
We break down complex database problems into clear, actionable steps. Through practical experimentation and early testing, your team learns to solve performance and scalability challenges quickly. No guesswork—just proven solutions based on real-world experience.
What our clients say​
"We were looking for a way to create database snapshots with ZFS/filesystem snapshotting. When I found out about DBLab, we started using it instead. The professional support we get from Postgres.AI is amazing, and the team is really to the point and deeply experienced in Postgres. We solved the problems we had when we started with the help of Postgres.AI."
"We chose to partner with Postgres.AI to enhance our database performance and build our internal expertise. Working with Postgres.AI has been insightful—the team brings a depth of expertise that's evident across consultations. While we're still implementing improvements, we've already seen benefits from a DBA perspective."
"The expertise of Nik and team at Postgres.AI has helped us significantly with the performance of our PostgreSQL database. Nik's understanding of PostgreSQL internals and ability to transfer his knowledge to us has helped prepare us for scale. Additionally, we use Row Level Security heavily, which is not a widely used feature. When we ran into some obscure performance issues with it, Nik was able to root cause it very quickly. This likely saved us weeks of time. Look forward to working with Postgres.AI in the future."
What to expect​
Our engagement is typically structured like this:
Immediate impact and systematic analysis​
- Quick resolution of urgent issues: Address problematic queries or recurring incidents to stabilize your database operations immediately.
- Comprehensive database health check: Use open-source observability tools and our proven methodology to identify and prioritize areas for improvement.
Optional follow-ups: long-term improvements​
- Streamlined processes: Implement essential practices such as incident management and zero-downtime schema changes.
- Tackling larger projects: Redesign database schemas, implement partitioning, perform major version upgrades, improve observability stack, start using logical replication, etc.
- Ongoing optimization: Establish routines for query analysis and optimization to maintain peak performance.
- Best practices adoption: Empower your team with the knowledge and tools needed to follow PostgreSQL best practices confidently.