In today’s data-driven enterprises, database performance issues can cascade into critical business disruptions within minutes. Yet traditional performance analysis remains locked behind a wall of technical complexity, requiring deep expertise in Oracle’s Automatic Workload Repository (AWR) and intricate knowledge of dozens of data dictionary views. Organizations face a critical bottleneck: performance problems demand immediate attention, but analysis often waits for specialized database administrators to become available.
With over 22 years of experience in Oracle database technologies, Chaitanya Kulkarni, Principal DevOps Engineer at Oracle America Inc, has been at the forefront of addressing this challenge. Working on Oracle’s Autonomous Database Serverless Team, Chaitanya Kulkarni has pioneered a groundbreaking solution that leverages SELECT AI, A powerful feature exclusive to Oracle Autonomous Database to transform how organizations approach database performance analysis.
The Challenge: Performance Analysis Locked Behind Expertise Barriers
Database performance analysis has traditionally been the exclusive domain of highly skilled DBAs who understand the complexities of Oracle’s performance data structures. Teams need to comprehend intricate table relationships across DBA_HIST_SQLSTAT, DBA_HIST_SNAPSHOT, and numerous other dictionary views. They must know precisely which columns to query, how to convert microseconds to seconds, and when to join with snapshot tables for accurate time-based analysis.
“This expertise barrier creates critical bottlenecks in modern operations,” explains Chaitanya Kulkarni, who has spent years optimizing Oracle database performance across enterprise environments. “Performance issues require immediate attention, but analysis often waits for available DBA resources. Development teams lack the visibility to proactively identify optimization opportunities, and business stakeholders struggle to understand database performance trends without extensive technical translation.”
When a critical application slows down, every minute of delay in identifying the root cause translates to revenue loss, degraded customer experience, and potentially cascading system failures.
Oracle Autonomous Database and SELECT AI: A Game-Changing Combination
Oracle Autonomous Database represents a fundamental shift in database management, combining machine learning and automation to deliver a self-driving, self-securing, and self-repairing database service. SELECT AI, exclusively available in Oracle Autonomous Database, takes this innovation further by enabling natural language queries against structured database content.
“Autonomous Database doesn’t just automate routine tasks it creates an intelligent platform that can integrate advanced AI capabilities like SELECT AI,” explains Chaitanya Kulkarni. “This combination of self-managing infrastructure with natural language processing creates unprecedented opportunities for democratizing database performance analysis.”
Rather than crafting complex SQL to analyze performance data, users can simply ask questions in plain English. When a developer asks, “Which SQL statements consumed the most CPU in the last hour?” SELECT AI transforms this question into accurate SQL and returns results in seconds no AWR expertise required. The system handles the complexity of joins, aggregations, and time conversions automatically, delivering precise performance data through an intuitive interface.
Transforming Database Operations with Natural Language
Chaitanya Kulkarni’s work with SELECT AI on Oracle Autonomous Database 26ai demonstrates the transformative potential of this technology. Complex performance analysis questions now execute through simple natural language requests. “Show me SQL with high buffer gets in the last 24 hours” automatically generates queries that aggregate buffer gets across AWR snapshots and filter by time range. “Show me historical SQL performance for sql_id xxxxxx” produces comprehensive SQL plan history. “Show me the top 5 wait events in the last 2 hours” delivers precisely formatted results for the most critical performance bottlenecks.
“These capabilities transform how teams approach database performance,” Chaitanya Kulkarni emphasizes. “What previously required specialized knowledge and multiple SQL queries can now be accomplished through intuitive questions that match how people naturally think about performance problems.”
The impact extends across multiple organizational levels. Development teams gain direct access to performance insights that were previously mediated through DBA resources. Operations teams accelerate incident response by enabling immediate performance analysis without waiting for specialized expertise. Business stakeholders can now understand database performance trends without requiring technical translation.
The Autonomous Database Advantage
The combination of Oracle Autonomous Database’s self-managing capabilities with SELECT AI creates powerful synergy for enterprise database operations. While Autonomous Database automatically handles patching, tuning, and backup operations, SELECT AI democratizes access to the performance insights generated by these automated processes.
“Autonomous Database generates comprehensive performance telemetry automatically,” Chaitanya Kulkarni explains. “SELECT AI makes this telemetry accessible to everyone who needs it, without requiring deep expertise in Oracle’s data dictionary structures.”
Organizations benefit from reduced operational overhead in multiple dimensions. Autonomous Database eliminates routine DBA tasks, while SELECT AI reduces the expertise barrier for performance analysis. Teams can deploy Oracle Autonomous Database, enable SELECT AI, and immediately begin leveraging advanced performance analytics without extensive database expertise.
Extending Capabilities with Oracle APEX
Building on the SELECT AI foundation, Customers can extend the capabilities through Oracle Application Express (APEX). This integration creates a comprehensive chatbot interface that further simplifies access to performance insights, with users able to interact with performance data through natural dialogue and visualize results through intuitive charts and dashboards all generated automatically from natural language requests.
“The APEX integration with SELECT AI can serve as the foundation for sophisticated business intelligence applications,” Chaitanya Kulkarni explains. “We’re not just enabling natural language queries; we’re creating complete analytical experiences that make database performance data accessible to everyone who needs it.”
Maximizing ROI: The Business Case for SELECT AI
The return on investment for Oracle Autonomous Database with SELECT AI extends across multiple dimensions. Organizations reduce time-to-resolution for performance issues by enabling immediate analysis without waiting for DBA availability. Development teams become more self-sufficient, reducing operational bottlenecks and accelerating development cycles.
“The ROI story is compelling because you’re getting value at multiple levels,” Chaitanya Kulkarni notes. “Autonomous Database reduces operational costs through automation and eliminates downtime through self-healing capabilities. SELECT AI then leverages the comprehensive performance data that Autonomous Database automatically collects, making it accessible to everyone who needs it.”
The technology also reduces training costs significantly. New team members can analyze performance data immediately without extensive Oracle expertise, accelerating time-to-productivity for new hires.
Chaitanya Kulkarni and the Future of Database Performance Analysis
As a Principal DevOps Engineer on Oracle’s Autonomous Database Serverless Team, Chaitanya Kulkarni brings deep expertise in database optimization, cloud technologies, and autonomous database management. His work on SELECT AI leverages years of experience managing database services with 99.99%+ uptime and developing advanced optimization solutions for enterprise environments.
Chaitanya Kulkarni’s contributions extend beyond implementation to thought leadership in the database community. He has presented research on SELECT AI and Oracle database technologies at IEEE conferences, sharing insights that advance the broader understanding of natural language database interfaces and performance optimization strategies.
“We’re at the beginning of a transformation in how organizations approach database performance,” Chaitanya Kulkarni reflects. “Oracle Autonomous Database provides the self-managing foundation, and SELECT AI extends its value by making performance insights accessible through natural language. This combination doesn’t replace DBA expertise it amplifies it, enabling organizations to scale their performance analysis capabilities across entire teams.”
As enterprises continue to generate increasingly complex workloads across distributed database environments, the ability to quickly analyze and optimize performance becomes ever more critical. For organizations seeking to reduce performance analysis bottlenecks, accelerate incident response, and empower broader teams with database insights, Oracle Autonomous Database with SELECT AI offers a proven path forward. With leaders like Chaitanya Kulkarni demonstrating its practical implementation and business value, this technology is poised to reshape how enterprises leverage their database performance data in the cloud era.
“The statements and opinions expressed here are my own and do not necessarily represent those of Oracle Corporation.”
