Index Optor
Auto-designing indexes via SQL analysis during development and recommending optimal indexes via efficiency analysis during testing and operation, driving rapid, comprehensive DB/SQL performance gains.
The Challenge: Top 3 Risk Factors in Index Operations
Limits of Manual Indexing & Performance Risks
Manually analyzing every table Access Path is practically impossible, and inappropriate or missing indexes lead to unexpected system outages.
Increased DML SQL Overhead
Excessive indexes designed solely for query speed degrade DML (Insert/Update/Delete) performance and cause severe system overhead.
Unused & Duplicate Index Waste
Unused or redundant composite indexes consume DB storage and drive unnecessary resource waste.
Core Specifications of Index Auto-Design & Optimization Guide
1
Verification DB-Based Index Optimization Simulation
Collecting clean SQL data from operational DBs and running independent optimization via virtual indexes in a test DB ensures zero load on the live system.
2
Execution Speed/IO Gain & Combined DML Impact Analysis
Accurately calculating pre/post improvements in Elapsed Time and Disk I/O (Buffer Gets), while simulating overhead impacts on INSERT/UPDATE/DELETE operations.
3
Unused/Duplicate Index Cleanup & Non-Stop DDL Migration Automation
Extracting obsolete indexes that waste space and strain systems. Ensuring zero downtime migration using isolated Tablespaces, optimized Parallel Degree, and Online DDL options.
Special Feature
Zero-Load Verification via Virtual Index
Temporarily binding Virtual Indexes via metastore session control before physical creation to achieve 99.9% accurate pre-calculation results.
Concept: Index Optimization Workflow Concept
Test
DB
SQL
Integration Test Stage
Operational
DB
SQL
Runtime SQL Collection
Optimal Index Auto-Design
Pre/Post-Optimization SQL Performance Simulation
Optimal Index Recommendation (Guide)
Procedure: Index Optimization Process
The INDEX-OPTOR engine supports a systematic 3-step process: Runtime SQL Collection, Optimal Index Design, and Quantitative Validation-Based Final Recommendations.
3
Optimal Index Recommendation
Index performance
simulation
SQL Performance Comparison
Current Index Env
Open POP Recommended Index Env
Optimal Index
guide
Add 23
Modify 4
Unused 1
2
Index optimization design
Access Path
analyze
Table size
NDV
Selectivity
=,>,<,between
Index Design
-
Add
Modify
Unused
1
Runtime SQL Collection
DB
Runtime SQL Collection
Evaluation: Quantitative ROI & Technical Superiority Verification
Response & I/O Improvement
DB Resource Usage
Drastic Short-Term Reduction
Index Optimization
Multi-Fold to 10x+ Performance Boost
-
DB Resource Savings
-
SQL Execution Speed Improvement
* Validated across multiple enterprise deployment projects
Repeatable index optimization across dev, test, verification, and ops stages
Rapid index optimization via optimal algorithm-based automation features
Opportunities to eliminate Unused indexes and resolve legacy index issues
Maximizing workforce efficiency & productivity via full-scale SQL index analysis
Optimal DB Index Auto-Design & Optimization Solution
A DB index optimization guide solution built on proven high-capacity database tuning expertise. Delivering optimal index guidance via index optimization simulations using zero-overhead Agent-less Data collection and innovative virtual application technology.