Solution
Even while you sleep, “Query Medic” continues to tune your poor-performing SQL.
AI-based SQL auto-tuning solution
Boost application performance, cut costs, and maximize customer satisfaction by optimizing your database performance
(Scheduled for release in Q3 2025)
AI-based SQL auto-tuning solution
It allows you to simultaneously prevent app performance failures by improving DB performance, reduce costs, and maximize customer service satisfaction.
(Scheduled for release in Q3 2025)
“Query Medic” is
Even when you are resting,
Performance degradation of SQL
“Extract ~ Tuning ~ Verification” 24*365
Automatically performs performance optimization tasks.
Are you experiencing this problem?
Operational perspective
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Lack of a system to verify the performance of developed SQL early
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Absence or lack of performance manager
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Difficulty in taking quick action on poor performing SQL
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Unverified App/SQL deployment causes unexpected performance issues
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Changes in DB environment (objects, statistics) can cause performance degradation and resource surges.
Cost perspective
Burden of repetitive DB resource expansion
High cost burden due to dependence on external tuning companies
Concerns about the high cost of using the cloud
Lack of analysis/address for unnecessary waste of resources
Reduced efficiency compared to investment in performance improvement
Service perspective
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Increased user dissatisfaction due to delays in app services
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Loss of business opportunities due to frequent DB performance failures
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Concerns about performance issues with new service launches
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App performance is unstable during new events/promotions
Comparison with existing methods
"Query Medic" presents a new paradigm in SQL tuning methods
Compare Items
People-based SQL tuning
General tuning support tools
(Oracle DB)
Query Medic
(QM)
SQL Tuning Subject
Performance Manager
Performance Manager
Query Madic AI (QM)
Selecting the SQL to be tuned
Handwork
Handwork
24*365 automatic extraction or developer request
SQL Tuning Point
When needed
When needed
24*365 None-stop auto tuning
SQL Tuning Support/Performance Method
Handwork
Varies by tool
(Hints/Index/Guide/Suggestions/Analysis Support)
AI-based automatic tuning
(Hints, indexes, refactoring, etc.)
How to apply the optimal index
Handwork
Varies by tool (supported/unsupported)
Automatic recommendation of optimal index
Index-related impact analysis
Handwork
doesn't exist
Automatic analysis of SQL performance changes related to indexes
Verify the consistency of results after tuning
Handwork
doesn't exist
Automatic verification of the same TuningSQL result values
Analysis of performance improvement (tuning) effects
Handwork
Varies by tool
(Supported at manual/SQL level)
Automatic comparison/analysis of performance improvement effects
(SQL/DB level)
SQL Tuning History Management
Handwork
doesn't exist
Automatic management of SQL tuning history
Support for automatic learning
doesn't exist
doesn't exist
Support for automatic learning of SQL performance optimization patterns
Effects of introducing Query Medic
AI-based automatic tuning can simultaneously achieve operational efficiency, cost reduction, and performance stabilization.
Operational efficiency
Repetitive SQL tuning tasks are automatically performed by AI 24 x 365, allowing performance managers to focus on value-driven tasks.
DB performance stabilization
Prevent service failures by proactively detecting and tuning poor-performing SQL and ensuring SQL quality from the development stage.
Improved Security & Trust
Reduce the risk of information leakage by reducing dependence on external vendor tuning, and increase IT reliability by reducing human errors through application of automatically verified SQL tuning results.
Cost savings
Minimize unnecessary resource expansion and optimize cloud costs by improving DB resource utilization efficiency.
Increase customer satisfaction
Increase user satisfaction, prevent customer churn, and strengthen business competitiveness with fast application speed.
Continuous performance improvement
The quality of tuned SQL improves over time by applying tuning patterns optimized for the customer environment through AI learning capabilities.
Key Features
“Query Medic” provides powerful features to automate the entire SQL tuning process.
Automatic selection (extraction) of tuning targets
It monitors SQLs running on the operational/verification DB 24 x 365 and automatically selects SQLs to be tuned. It also handles tuning of SQLs requested by developers in real time.
Automatic verification of tuning results (values)
Automatically verifies that tuned SQL returns the same results as original SQL, ensuring data consistency.
Performance improvement performance reporting
It clearly compares and analyzes the performance improvement effects and results before and after tuning, and provides information such as tuning history and tuning results/statistics in a dashboard.
AI-based automatic tuning
QM AI automatically tunes the extracted SQL by applying various techniques such as hint changes, index recommendations, and refactoring. No human intervention is required throughout the tuning process.
Index application impact analysis
Minimize risk by simulating and analyzing the performance impact on other SQLs when adding/changing indexes required for tuning in advance.
User friendly UI/UX
It provides an intuitive interface that even tuning non-experts can easily understand and use, as well as functions to set various tuning options and environments.
How it works
“Query Medic” ’s AI-based SQL automatic tuning and verification process.
Query Medic Features
“Query Medic” automatically extracts, tunes, and verifies target SQL for tuning 24 x 365.
24x365 fully automated
From extracting target SQL to tuning and verification, it is performed automatically without human intervention.
Related SQL Performance Impact Analysis
It provides results that analyze the performance change impact on all related SQLs when adding or changing an index, helping performance managers quickly determine whether to apply tuning SQL.
Continuous learning features
Improve the tuning quality of SQL by continuously learning SQL tuning patterns in AI models.
LLM-based SQL tuning
By leveraging AI models, SQL performance is optimized in various ways, such as changing hints for the target SQL, changing indexes, and refactoring SQL.
Automatically validate tuning SQL
Query Medic automatically verifies the performance improvement effect of tuning SQL and the consistency of data result values, providing reliable results.
User friendly UI/UX
It provides an intuitive interface that even tuning non-experts can easily understand and use, as well as functions to set various tuning options and environments.