Data Fundamentals
This overview orients you to the essential building blocks behind most data decisions: how you model information, enforce correctness under concurrent access, make reads fast, reason about consistency, and manage data through its lifecycle. Use this page as a map to the child articles—each one goes deeper with examples and trade‑offs.
Mental model
What’s in scope
- Data modeling: choose the right abstractions and shape at the conceptual, logical, and physical levels.
- Transactions & isolation: maintain invariants under concurrency—see Transactions & Isolation Levels.
- Indexing & queries: accelerate access paths—see Indexing & Query Optimization.
- Consistency models: align semantics with system realities—see Consistency Models.
- Lifecycle: plan retention, archival, and deletion—see Data Lifecycle.
How to use this section
- Start with Data Modeling to frame entities, relationships, and access patterns.
- Ground concurrency guarantees in Transactions & Isolation Levels; pair with budgets in Quality Attributes.
- Match access paths to workload using Indexing & Query Optimization.
- Set correct expectations across services with Consistency Models and the sibling overview Basic Distributed Systems Concepts.
- Close the loop with Data Lifecycle and deeper topics in Data Architecture & Persistence.
Related topics
🗃️ Data Modeling
3 items
📄️ Transactions & Isolation Levels
TBD.
📄️ Indexing & Query Optimization
TBD.
🗃️ Consistency Models
3 items
📄️ Data Lifecycle
TBD. Ingest → process → store → serve → archive.