Data & Storage System Designs

Worked Data & Storage system design walkthroughs: the requirements, the trade-offs, real numbers and the component choices behind each design.

Browse all system designs

  1. ACID Transactions and Isolation Levels

    A deep dive into ACID guarantees, isolation levels, and the real trade-offs engineers face when choosing consistency vs. throughput in relational and distributed databases.

    Data & Storage · intermediate · 12 min read

  2. Bloom Filters and Probabilistic Data Structures

    How Bloom filters, Count-Min Sketch, HyperLogLog, and friends let you trade a small, bounded error rate for orders-of-magnitude savings in memory and latency.

    Data & Storage · intermediate · 12 min read

  3. Change Data Capture and the Outbox Pattern

    Reliably stream database mutations to downstream systems using CDC and the transactional outbox pattern, eliminating dual-write inconsistencies at scale.

    Data & Storage · advanced · 12 min read

  4. Consistent Hashing and Virtual Nodes

    How consistent hashing minimizes key remapping during cluster changes, and how virtual nodes (vnodes) distribute load evenly across heterogeneous hardware.

    Data & Storage · intermediate · 12 min read

  5. Data Replication: Master-Slave, Master-Master, Quorum and Replication Lag

    A deep dive into database replication topologies, consistency guarantees, lag mechanics, and the real trade-offs engineers face when choosing between them.

    Data & Storage · intermediate · 12 min read

  6. Database Federation and Denormalization

    Split a monolithic database into purpose-built federated stores and use denormalization to eliminate cross-service joins, trading write complexity for read speed and operational independence.

    Data & Storage · intermediate · 12 min read

  7. Database Indexes: B-trees, Hash, Composite, and Covering

    A deep dive into how B-tree, hash, composite, and covering indexes work internally, when to use each, and the real costs they impose on reads, writes, and storage.

    Data & Storage · intermediate · 12 min read

  8. Database Scaling Strategies: Read Replicas, Caching, Partitioning, and CQRS

    A deep-dive into the four core database scaling patterns—read replicas, caching layers, horizontal partitioning, and CQRS—with real trade-offs, failure modes, and interview talking points.

    Data & Storage · advanced · 12 min read

  9. Database Sharding: Strategies, Rebalancing, Hot Spots, and Cross-Shard Queries

    A deep-dive into horizontal partitioning strategies, shard rebalancing, hot-spot mitigation, and the cost of queries that span multiple shards.

    Data & Storage · advanced · 12 min read

  10. Database Types: Key-Value, Document, Wide-Column, Graph, Time-Series and Search

    A practical guide to the six major NoSQL database families — when to use each, how they store data, and how to choose the right one for your workload.

    Data & Storage · beginner · 12 min read

  11. SQL Tuning: Query Plans, Indexing, Connection Pooling, and Schema Design

    A deep-dive into making relational databases fast at scale: reading EXPLAIN output, choosing indexes, sizing connection pools, and designing schemas that survive growth.

    Data & Storage · intermediate · 12 min read

  12. SQL vs NoSQL: Choosing a Database

    A concrete guide to picking between relational and non-relational databases, covering data models, consistency guarantees, scaling patterns, and when each family wins.

    Data & Storage · beginner · 12 min read