The 2020-born Pennsylvania-based startup providing automated performance tuning solutions for data-intensive applications, Ottertune, has just recently announced bagging $12M in its ended Series A round. This funding round was led by Intel Capital alongside Race Capital with participation from Accel. Intel Capital’s Senior MD Nick Washburn join the startup’s board, assisting to accelerate the company’s growth.
How Ottertune is shaping the Database Management Market
Database management is a growing multi-billion dollar market with systems bearing hundreds of configuration settings actively affecting performance and cloud costs. OtterTune’s purpose in this market is to provide automated performance tuning solutions for data-intensive applications. Its AI & ML engines learn how a database behaves, continually tuning runtime knobs to improve the system’s performance. Machine learning is applied to safely analyse and continuously optimise those settings to assist organisations of all sizes to run their databases more efficiently at a lower cost.
Intel Capital’s Nick Washburn stated, “Databases are the bedrock of all applications, and OtterTune is accelerating the journey for companies of all sizes to autonomously optimise this critical component of their tech stack, driving performance, managing cost, and ultimately ensuring reliability.”
By automating the complex and time-consuming process of database performance optimisation, OtterTune has provided cloud teams with peace of mind and time to focus on other priorities. Daniel Rodgers-Pryor, CTO of educational technology platform developer Stile Education testified to this commenting, “OtterTune keeps our databases running smoothly, and it has removed the risk and research time associated with manual tuning. With OtterTune in place, our team can focus more on new development, and be much less distracted by database administration.”
What happens when ML meets Database?
Ottertune is what happens! The startup was founded by Andy Pavlo, Bohan Zhang and Dana Van Aken who are multidisciplinary experts at the intersection of database and machine learning fields as evidenced by their cutting-edge research while at Carnegie Mellon University.
The platform works for cloud-based PostgreSQL and MySQL databases (Amazon RDS and Amazon Aurora). OtterTune’s service just recently commenced its support for Amazon Aurora databases, as well as Amazon RDS databases. In addition, the platform also offers database health checks that mitigate outages & performance drops. The company will use the new round of financing to expand its engineering team and build support for additional databases on other cloud platforms as well as innovate additional autonomous optimisation features.
The Pittsburgh startup also just announced its first-ever human vs. OtterTune Database tuning contest to be held in September this year. This bout will match OtterTune’s automated approach to database optimisation against an expert human database administrator. The competitor achieving the most significant database performance improvement will be crowned the Relational Riverside Rumble 2022 winner as well as being rewarded with a $10,000 cash prize.