Complete Guide

Documentation

Everything you need to get started with DBOpt AI, best practices, security architecture, and all 22 powerful database analysis features.

Quick Start

Get Started in 3 Simple Steps

Start analyzing your database in under 5 minutes with our intuitive setup process

1

Create Account

Sign up for your free 14-day trial. No credit card required to get started. Access all 22 analysis features immediately.

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2

Connect Database

Add your database connection securely. We support PostgreSQL, MySQL, MariaDB, Oracle, and SQL Server with AES-256 encryption.

Credentials encrypted at rest
SSL/TLS support
3

Run Analysis

Select from 22 analysis features and get AI-powered recommendations in seconds. Export results as JSON, CSV, or PDF.

⚡ Results in 5-30 seconds

Supported Database Engines

PostgreSQL
9.x - 16.x
MySQL
5.7+, 8.x
MariaDB
10.x+
Oracle
11g+
SQL Server
2016+
Best Practices

Database Analysis Best Practices

Expert tips to get the most accurate insights from DBOpt AI

🎯 When to Run Analysis

  • 1
    Before Peak Hours: Run analysis during off-peak times to minimize impact on production workloads
  • 2
    After Schema Changes: Always analyze after migrations or schema updates to catch new issues
  • 3
    Weekly Reviews: Schedule weekly analysis to track performance trends over time

⚡ Optimize Analysis Speed

  • 1
    Use Read Replicas: Point DBOpt AI to read replicas to avoid impacting your primary database
  • 2
    Focus Analysis: Start with specific categories (e.g., Index Optimization) before running all 22 features
  • 3
    Enable SSL: Use SSL connections for remote databases to ensure secure data transmission

🔒 Security Recommendations

  • 1
    Read-Only Access: Create dedicated read-only database users for DBOpt AI connections
  • 2
    IP Whitelisting: Restrict database access to DBOpt AI's IP addresses
  • 3
    Rotate Credentials: Update database passwords quarterly and update in DBOpt AI

📊 Interpreting Results

  • 1
    Start with Critical: Prioritize "Critical" and "High" severity issues before addressing warnings
  • 2
    Test First: Always test recommendations in staging before applying to production
  • 3
    Track Metrics: Compare before/after metrics to measure the impact of optimizations
Security Architecture

Bank-Level Security

Three-layer security architecture protecting your database credentials and sensitive data

Level 1: Credential Encryption

CORE
AES-256-CTR Encryption

Military-grade encryption for all database credentials stored in DBOpt AI

PBKDF2 Key Derivation

100,000 iterations for secure key generation from master password

Unique Salt & Nonce

16-byte cryptographically random salt and nonce per connection

Level 2: Message Authentication

INTEGRITY
HMAC-SHA256 Verification

Every encrypted credential includes an HMAC signature to detect tampering or corruption

Replay Attack Prevention

Unique nonce values prevent attackers from reusing intercepted encrypted data

Level 3: Storage & Transmission

TRANSPORT
Encrypted Database Storage

All credentials stored encrypted in PostgreSQL, never in plain text

HTTPS/TLS Encryption

All API communication encrypted in transit with TLS 1.3

SSL Database Connections

Optional SSL/TLS for connections to your target databases

Certified & Compliant:
SOC 2 Type IIGDPRISO 27001HIPAA

22 Analysis Features

Comprehensive database intelligence across 5 key categories

Index Optimization

  • Unused Index Detection
  • Missing Index Suggestions
  • Partition Recommendations

Security & Compliance

  • Security Audit
  • Security Scores
  • Vulnerability Detection
  • Weak Password Detection

Performance Analysis

  • Configuration Analysis
  • Slow Query Detection
  • Query Rewrite Suggestions
  • Bottleneck Identification

Workload & Capacity

  • Workload Analysis
  • Time-Based Patterns
  • Capacity Planning
  • Historical Trends
  • Data Model Analysis

Maintenance & Recovery

  • Vacuum Analysis
  • Maintenance Scheduling
  • Backup Health Monitoring
  • Replication Status
  • Anomaly Detection

Ready to Get Started?

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