OtterTune

Explore how Neural Network (NN)-based solutions are transforming DBMS configuration tuning. 

Unlock Smarter DBMS Tuning with Neural Networks

Discover how Bayesian Optimization is revolutionizing DBMS configuration, making tuning faster and smarter for better performance.

How Bayesian Optimization Speeds Up DBMS Tuning 

Use historical workload data and similarity techniques to speed up DBMS tuning, reduce training time, and optimize configurations more efficiently. 

Why Re-invent the Wheel? Use Past Workloads for Smarter DBMS Tuning

Learn about configuration-level pruning techniques for DBMS tuning, including SRCC, PCA, LASSO, Random Forest, and HeSBO. 

How Configuration-level Pruning Reduces Optimization Time in DBMS Tuning

Learn about runtime-based workload characterization in DBMS tuning, including metrics like query cache utilization, memory allocation, and locking overhead. 

Prune Your Way to Better Database Management System Performance

Runtime-Based Workload Characterization in DBMS Tuning

OtterTune automatically optimizes the configuration of Amazon-based PostgreSQL and MySQL databases to improve performance, reduce costs and maintain healthy operations.

OTTERTUNE

ottertune.com

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Since 2020

OtterTune's stories on HackerNoon

Unlock Smarter DBMS Tuning with Neural Networks

How Bayesian Optimization Speeds Up DBMS Tuning

Why Re-invent the Wheel? Use Past Workloads for Smarter DBMS Tuning

How Configuration-level Pruning Reduces Optimization Time in DBMS Tuning

Prune Your Way to Better Database Management System Performance

Runtime-Based Workload Characterization in DBMS Tuning

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