storage-engines

Included with Lifetime

$97 forever

Storage-engine and database-internals architecture: B-tree vs LSM-tree, write- ahead logging, buffer/page cache, MVCC and concurrency control, durability/fsync, and compaction. Architect-level engine selection and data-path design. USE WHEN: designing or choosing a storage engine, "B-tree vs LSM", "WAL", "buffer pool", "MVCC", "compaction", "write amplification", "fsync/durability", embedded KV store, database internals, read/write-optimized store choice. DO NOT USE FOR: SQL query writing/ORM (use database/orm skills); data pipelines (use `data-intensive`); vector indexes (use vector-stores skills).

Design

What this skill does

# Storage-Engine Internals

## B-tree vs LSM-tree — the defining choice

| | **B-tree** (InnoDB, Postgres) | **LSM-tree** (RocksDB, Cassandra) |
|---|---|---|
| Writes | In-place; random I/O; write-amp from page writes | Sequential (memtable→SST); high throughput |
| Reads | 1 path, predictable | May touch many levels → read-amp (mitigate w/ bloom filters) |
| Space | Fragmentation | Space-amp until compaction |
| Best for | Read-heavy, range scans, point lookups | Write-heavy ingest, SSD-friendly |

The three amplifications (**write / read / space**) trade off against each other —
state which one the workload can least afford.

## Durability & the write path

- **WAL**: append before applying; `fsync`/`fdatasync` policy = the
  durability ↔ throughput knob (group commit amortizes fsync). `O_DIRECT` vs
  page cache; `fsync` correctness (don't trust it lying — the "fsync-gate").
- **Buffer/page cache**: hit ratio drives everything; eviction (LRU/CLOCK),
  dirty-page writeback, checkpointing to bound recovery time.
- **Crash recovery**: redo/undo, ARIES, checkpoints; recovery time vs steady-state.

## Concurrency control

- **MVCC** (snapshot reads, no read locks) vs 2PL (locking) vs OCC (validate at
  commit). MVCC needs version GC/vacuum (Postgres bloat).
- Isolation levels and their anomalies; SSI for serializable without heavy locks.

## When to recommend what
- Write-heavy ingest / time-series / SSD → LSM (RocksDB/Cassandra/ScyllaDB).
- Read-heavy, rich queries, range scans → B-tree (Postgres/InnoDB).
- Embedded/edge KV → LMDB (B-tree, mmap) or RocksDB (LSM) by read/write mix.

Files: 1

Size: 2.3 KB

Complexity: 16/100

Category: Design

Source: https://github.com/claude-dev-suite/claude-dev-suite/tree/main/skills/systems/storage-engines

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