We have spent over two decades working with databases — not just using them, but building infrastructure around them, tuning them at scale, and contributing to the PostgreSQL ecosystem. When you work with SolidStateDB, you get that depth from day one.
Every engagement starts with understanding your system — not applying a generic playbook to it.
Not sure where to begin? A health check gives you a clear picture of where your database stands — before committing to anything longer-term. We review your single node or cluster and deliver a written report with prioritised findings and specific next steps.
Query plans, index strategy, cost parameters, JIT, parallelism, vacuum tuning — the full picture. We read EXPLAIN ANALYZE output and tell you what's actually wrong, not what a configuration generator suggests.
Ongoing database operations without the overhead of a full-time hire. Proactive monitoring, incident response, version upgrades, backup validation, and a direct line to engineers who know what they're looking at.
Oracle to PostgreSQL, MySQL to PostgreSQL, cloud to on-prem, or on-prem to cloud. We handle schema conversion, data validation, and the edge cases automated tools miss — because we've seen what breaks in production.
High availability, replication topologies, Patroni, CloudNativePG, connection pooling, and distributed setups. We help you design for the failure modes you haven't encountered yet.
Production incidents don't keep office hours. When your database is down or degraded, you need an engineer who can diagnose and act — not a ticketing queue. We offer direct emergency access for critical situations.
Most database consultants work with PostgreSQL. We've spent careers working on it — contributing features, shipping enterprise tooling, and running it in production across every major cloud and deployment model.
Decades of core infrastructure development in the PostgreSQL ecosystem — pgpool II, BART backup tooling, FDW architecture, replication, and more.
We know how RDS, Aurora, Aiven, and CloudNativePG differ from upstream PostgreSQL — and why those differences matter for your specific tuning and architecture decisions.
Not what a configuration generator recommends. We read query plans, study your workload pattern, and give you a specific diagnosis — not a checklist lifted from a blog post.
You work with the founders. No account managers, no junior engineers handed your problem. The people you talk to are the people doing the work.
There is a version of database consulting that is mostly about running a configuration generator and reading back the output. We have nothing against tools — we have built some ourselves.
But a query that takes 4 seconds on your system might take 4 milliseconds on a different storage type. A parameter change that every guide recommends can trigger a cascade of side effects your specific workload hits hard.
You only learn this after seeing enough systems fail in enough different ways. That is what we bring to the table.
— The SolidStateDB teamWe are not an AI company. We are database engineers who use AI tooling the right way — to move faster, surface patterns earlier, and give you better answers. The judgement is still ours.
The database world is changing. AI assistants are being asked to diagnose slow queries, review schemas, and suggest configuration changes. Most of them get it wrong — not because the models are bad, but because they lack grounded, accurate PostgreSQL knowledge at the point of inference.
We are building the infrastructure to fix that. And we are offering it as part of our consulting practice now.
We set up and configure a PostgreSQL MCP (Model Context Protocol) server for your environment — letting AI assistants like Claude or Cursor connect directly to your database, read live query plans, inspect pg_stat_statements, and reason over real schema and performance data.
The result: your AI assistant stops guessing about your database and starts working with actual evidence.
Generic AI models give generic database answers — often wrong for your specific PostgreSQL version, cloud provider, or workload. We build a retrieval-augmented generation layer grounded in accurate PostgreSQL documentation, your own runbooks, and curated expert knowledge.
Your team gets an AI assistant that actually knows your stack — not one that hallucinates pg_tune output.
We combine our manual diagnosis with AI-powered pattern matching across your query history, wait events, and configuration drift. This lets us surface problems faster — not replace the engineer who knows what to do with them.
Think of it as a force multiplier: the same expert depth, with better visibility across your entire workload at once.
All AI-assisted work is reviewed and validated by our engineers before it reaches you. We have spent years benchmarking AI recommendations against real workloads — we know where they are reliable and where they are not.
Whether it's a specific performance problem, a migration you're planning, or you want a second opinion on your architecture — we're happy to have an honest conversation. No sales pitch, no obligation.