What are the best tools for analyzing and optimizing database performance?

Operating system performance tools can help us analyze operating system-level performance and can provide useful information to the administrator to investigate problems with operating system-level resources.

The primary tools are SolarWinds DBPA, SQL Power Tools, and Paessler PRTG Network Monitor. These tools can help to analyze and monitor the performance of different databases. These tools are responsible for watching different indicators e.g query performance, system throughput, that become efficiency tools. Aside from this, Microsoft also has some performance monitoring solutions like the Windows Performance Summarizer that can be used to visualize system resource usage and ultimately helps with performance analysis of SQL Server. It makes all the difference to get the right tool for the task in order to fit with your current IT infrastructure and also for successful collaboration between assigned functions.

There are two keys to understanding performance monitoring. The first is that you can't focus on any one metric. Sure, duration, how long a query runs matters. However, most of us hit input/output (I/O) problems with our disks before anything, so monitoring for I/O is as important as duration. Same goes for CPU & Memory. You need all of them, not just one. Plus, you also need execution counts on the queries because this adds to all the other metrics. Second, you must have two points of data. Yesterday and today, before and after a deployment. Whatever. You can't know something is slow or fast until you have something to compare it with.

Dynamic management views and dynamic management functions that will help us to monitor the health and performance of SQL Server instance.

Performance monitoring involves the measurement of performance over time against indicators of performance or key performance indicators (KPIs).

Performance issues in databases can come from improper server configuration, hardware misconfiguration, poor data structures, bad or missing statistics, and bad or missing indexes. However, the number one cause is absolutely your code. Most of the issues will be in your code and this leads to one inescapable issue: You're going to need to change that code in order to see performance improve. The most common request is for us to find a switch, a knob, a setting, an index, anything to improve performance without touching the code. However, if we really want to improve performance, we must be prepared for code changes. Avoiding this will just prolong the issues we're facing.

In my daily life as a DBA, my main focus is optimizing database performance. For this, I frequently use tools such as SQL Profile for SQL Server and EXPLAIN for Oracle and PostgreSQL. However, I recognize that detailed analysis and understanding of the highest cost query execution plan are essential steps to ensuring significant results in terms of performance.

leading on from this - I very much agree about the code but having recently coded I would say the reasons for this are plentiful! When you code you very rarely have a full data set or the workload that a production server does! One of the things to bear in mind is that often people use one database instance to do OLTP, reporting different apps using the same resources and incredibly to avoid licensing they have SSAS at the same time! Needless to say tuning mixed workloads is like the hydra you cut off one head and three grow back! Another thing is that often people use the default transaction isolation level , which is not always necessary! the CAP theorem should be looked at with the data and not everything needs concurrency!!

Tools for database performance optimization include monitoring tools like New Relic, query profilers such as pg_stat_statements, tuning advisors like Oracle's SQL Tuning Advisor, indexing tools, and benchmarking tools like Sysbench. These tools offer insights, identify bottlenecks, optimize queries, and simulate workloads for improved performance.

Query optimization is the process of selecting an efficient execution plan for evaluating the query. After parsing of the query, parsed query is passed to query optimizer, which generates different execution plans to evaluate parsed query and select the plan with least estimated cost

Do not just create index, when creating an index in a database, consider these key factors: Selectivity: Indexes are more efficient if the column values are unique. Query Patterns: Create indexes on columns frequently used in WHERE clauses, JOIN conditions, or ORDER BY. Index Type: Choose from B-tree, hash, full-text, or spatial indexes based on data and query needs. Write and Update Overhead: Indexes can slow down write operations as they require updates. Storage Space: More indexes mean more disk space usage. Maintenance: Regular maintenance is needed to manage index fragmentation and efficiency.

To address slow query execution, you typically want to create indexes or verify that indexes are being used by a query. In particular, you typically perform the following tasks: Create a database index for the most selective column in the query. Possibly create a database index for other columns.

Definitely, indexing will not always have a positive effect. Therefore, indexing should be effective and accompanied by complete knowledge of the business system

DBeaver: This database management tool provides index management features, allowing users to analyze existing indexes and create new ones for optimal query performance. Oracle SQL Developer (for Oracle Database): It includes tools for index tuning advisor that suggest improvements to existing indexes to enhance performance.

Identify inefficient indexes using tools like Oracle SQL Developer or SQL*Plus and consider creating, modifying, or dropping indexes based on query performance and access patterns. Implement Index Compression to reduce storage overhead and improve query performance for large tables with frequent access.

MySQL Workbench (for MySQL): It offers resource management features like performance schema for monitoring resource usage and MySQL Enterprise Monitor for proactive management. SQL Sentry: This tool provides comprehensive performance monitoring and resource management for various databases, including SQL Server and Oracle.

Configure Oracle Resource Manager to allocate resources fairly among different users and applications based on resource utilization policies and priorities. Use Database Resource Manager to control resource consumption for different database operations such as parallel queries, DML statements, and PL/SQL procedures.

Workload analysis is an ongoing process that drives continuous improvement in database performance. Regularly monitoring and analyzing workloads allow administrators to identify emerging performance trends, evaluate the effectiveness of optimization efforts, and adjust strategies accordingly to maintain optimal performance.

Analyze Automatic Workload Repository (AWR) reports and Automatic Database Diagnostic Monitor (ADDM) findings to identify performance trends, top SQL queries, and resource-intensive operations. Use SQL Performance Analyzer to compare the performance impact of system changes (like parameter tuning or index creation) on SQL workloads.

What is a workload analysis? Workload analysis is a method you use to calculate how many people you will need to cover a certain project. It is also a method used for drilling into the current workload of your teams so you can make adjustments and predict how that workload could change in the nearest future.

Percona Monitoring and Management (PMM): PMM offers workload analysis tools like Query Analytics, which helps in identifying and optimizing high-load queries for better performance. SQL Server Profiler (for Microsoft SQL Server): It allows users to capture and analyze workloads to identify performance bottlenecks and optimize queries accordingly.

Automated tuning is amazing. We're seeing more and more functionality based on machine learning and even AI that is allowing our database systems to be automatically improved. However, AI will not automatically improve a bad database design. If you have improper table structures, bad data definitions, and other issues, no amount of query tuning automation is going to help. While automatic tuning is going to help us immensely, we still must pay attention to the fundamentals of database design in order to set up the automatic tuning for success.

Control systems are tuned to meet your specific performance and robustness goals subject to feasibility constraints such as actuator limits, sensor accuracy, computing power, or energy consumption. The library of tuning goals lets you capture these objectives in a form suitable for fast automated tuning

Tuning Advisor (for Microsoft SQL Server): It's an automated tool that analyzes query workloads and suggests indexes, statistics updates, and other performance optimizations. MySQLtuner: This Perl script provides automated recommendations for tuning MySQL configurations based on system usage and workload analysis.

Schedule Automatic Database Diagnostic Monitor (ADDM) analysis to proactively identify performance issues, generate recommendations, and implement tuning actions automatically. Consider using SQL Access Advisor to recommend indexes, materialized views, and partitioning strategies to optimize query performance.

Canary queries! As I was a DBA in early part of my data career let me explain this with relevant examples: 1. To analyze any database performance, one should always go with the native utilities provided by the database vendor. For instance, Teradata had a windows utility called Performance Monitor (PMon) and its corresponding web version called viewpoint. 2. Some of the native performance analysis tools come with options to optimize or recommendations to implement. For example, stale statistics collection or fixing indexes. 3. If such utilities are not enough, developing in-house utilities using native APIs is better or custom queries like canary queries to run at regular intervals. 4. Auto tuning helps but is not enough many a times.

Start with minimal tools from OS and Database , try to understand the application. In case of Oracle perform a workload comparison with AWR Diff

Creo que no puedes basarte solo en uno de los puntos que se muestran en las respuestas. Es necesario tener monitorización de todos esos puntos, un proceso correcto para detectar de forma proactiva si algo está perdiendo calidad o dando menos rendimiento y, finalmente, un buen equipo humano interno o externo que tenga la capacidad de entender los datos y las alertas de las herramientas.

Leverage Oracle Performance Tuning Packs for advanced performance tuning features like Real-Time SQL Monitoring, SQL Plan Management, and SQL Performance Analyzer. Explore Oracle Database Performance Tuning Guide and Best Practices for detailed insights into performance tuning methodologies, tools, and techniques.