Why DBtune
DBtune is an AI-powered database optimization service that automatically tunes PostgreSQL runtime parameters for optimal performance. Implementations of DBtune on-premises, in the cloud, and in SaaS environments show between 50% and 1000% improvement.
DBtune uses an agentic AI optimization approach to analyze your database's unique workload in real-time to generate the optimal configuration, delivering peak performance in a matter of hours.
Customers come to DBtune for performance optimization, increased operational efficiencies, and to optimize database spend.
Boost database performance by up to 250%
Database performance optimization, commonly expressed as transactions per second (TPS), average query runtime (AQR), and query latency for 99% of the queries (P99), helps DBAs and application architects measure the overall performance and is key to user satisfaction. These metrics characterize workload performance, that is, how long a user has to wait for a response and how many concurrent users the system can support while still meeting its SLA requirements. This implies that the tuning approach has to be aware of the workload, the number of users, the type of requests, and the data volume.
While the actual DBtune results for a specific database server depend on the workload, our experience shows that customers can expect between 50% and 250% improvement of TPS, AQR, and P99. Some users even reported between 5.6 and 13-fold performance improvements!
Increase DBA efficiency by 10x
Increased operational efficiency, especially the ability of DBAs and SysOps teams to manage a growing PostgreSQL estate, is the second reason customers come to DBtune. Depending on the workload, DBtune can optimize a server within 120-180 minutes, requiring about 15 minutes of DBA focus time. That is a fraction of the time that would be required to tune the database manually. DBtune-supported DBAs are much more productive than their non-AI-supported peers, and what is extremely important, with DBtune, they can adjust and retune systems continuously with minimal effort. The future of databases is AI-assisted.
Do more with less total database spend
Managing database spend benefits significantly from database tuning. Databases usually represent a significant part of the IT spend on-premises or in the cloud. Well-tuned databases require less CPU, less IO, less storage, fewer licenses, and they reduce support costs. Periodic tuning improves the stability and high availability, and it creates headroom for future growth in data, users, and workload. It also provides the opportunity for workload consolidation, e.g., moving more databases or more users onto the same server, further reducing OpEx and CapEx.
Who is DBtune for?
DBtune was created to help customers successfully use PostgreSQL at scale.
- 1. DBAs using DBtune can manage more servers with less effort, while moving from reactive firefighting to proactive, strategic performance optimization.
- 2. Application developers and DevOps engineers can eliminate database bottlenecks from the start and ensure that the infrastructure is tuned for performance.
- 3. CTOs and database leaders maximize their investment in PostgreSQL and lower their cost, improving the operating margins and the market capitalization of their companies while equipping the team with tools that drive efficiency and innovation.
DBtune integrates deep database expertise with practical application of AI and Machine Learning. The team is led by notable experts in AI and Machine Learning, and complemented by some of the most experienced PostgreSQL leaders.
The creator of the DBtune AI engine
Dr. Luigi Nardi is a pioneering force in the application of artificial intelligence to database systems. Armed with a Ph.D. in Computer Science from Pierre and Marie Curie University in Paris, his academic research at Stanford University and Imperial College London, and his professorship in AI at Lund University, he laid the groundwork for a revolutionary approach to a long-standing industry problem: database tuning.
Nardi champions the use of advanced AI, Machine Learning, and optimization methods to automate and perfect database server configuration. He directly challenges the status quo of tedious manual tuning, delivering intelligent systems that autonomously navigate complex parameter optimization spaces to achieve peak performance. His work doesn't just improve efficiency; it redefines the operational standards for massive-scale database management.
Now a key leader in the tech industry, Nardi’s impactful research and practical implementations have established him as the authority on AI-driven database optimization, setting the new benchmark for performance and scalability.
The PostgreSQL authority
Magnus Hagander stands as a Major Contributor to the PostgreSQL community, a leader whose technical authority and decisive contributions have directly shaped the database's enterprise capabilities. He is one of the seven PostgreSQL Core Team members whose influence extends from deep code-level enhancements to high-level community stewardship as President of PostgreSQL Europe.
Hagander’s expertise is acutely focused on the critical intersection of performance, security, and reliability—key pillars of effective database tuning. His work on features like advanced authentication and robust high-availability solutions provides the essential foundation upon which stable and performant systems are built. He doesn't just suggest improvements; he architects and implements them.
Asserting the necessity of professional-grade tooling, Hagander’s collaboration with DBtune is a strategic alliance. This partnership bridges the gap between the deep, internal tuning knowledge of a PostgreSQL expert and the power of AI-driven optimization. By lending his unparalleled insight into the PostgreSQL engine, he helps ensure that AI tuning recommendations from DBtune are not just theoretical but are practical, robust, and authoritative. His role is to guarantee that automation meets the exacting standards of the world's most advanced open-source database.