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"Database Decision Tree"

"An interactive tool that helps engineers choose the right database for their use case through guided questions and real-world examples"

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Database Decision Tree

Choosing the right database is one of the most critical architectural decisions in any project. This interactive tool guides you through key questions to help you select the optimal database for your specific use case.

Try It Out

Choose Your Database

What type of data system do you need?

First, let's determine if you need a primary database, a caching layer, or a complete application backend platform.

Features

  • •20+ Database Options: Comprehensive coverage of SQL, NoSQL, embedded, distributed, vector, and specialized databases
  • •Real Performance Numbers: Actual benchmarks and metrics from 2024 for informed decisions
  • •Company Case Studies: See how Discord, Instagram, Netflix, and others use each database at scale
  • •Cost Indicators: Visual indicators for pricing, operational complexity, and learning curves
  • •Migration Guidance: When to move from one database to another based on scale triggers

How It Works

The decision tree asks about:
  1. •Your primary use case (caching, primary database, backend platform)
  2. •Data access patterns (key-based, relational, time-series, etc.)
  3. •Scale requirements (from embedded to global scale)
  4. •Consistency vs availability trade-offs
Based on your answers, it recommends specific databases with:
  • •Performance profiles with real numbers
  • •Companies using it at scale
  • •When to use vs when not to use
  • •Migration triggers for future growth

Technical Implementation

Built with:
  • •React & TypeScript for type-safe interactivity
  • •Tailwind CSS for responsive design
  • •Tree data structure for efficient navigation
  • •Decision history tracking with breadcrumb navigation

Databases Covered

SQL Databases

  • •PostgreSQL, MySQL, SQL Server, CockroachDB, Google Spanner

NoSQL & Wide-Column

  • •ScyllaDB, Cassandra, MongoDB, DynamoDB

Specialized

  • •Redis (caching), Elasticsearch (search), ClickHouse (analytics), Neo4j (graph)

Modern Solutions

  • •Vector databases (Pinecone, Weaviate, pgvector)
  • •Embedded databases (SQLite, DuckDB, RocksDB)
  • •Backend platforms (Firebase, Supabase)

Future Enhancements

  • •Side-by-side database comparison mode
  • •Export recommendations as PDF/Markdown
  • •Cost calculator based on workload
  • •Community-contributed decision paths