Illustration comparing a B‑Tree node and an LSM‑Tree level.

Why LSM Trees Outperform B-Trees for Write‑Intensive Workloads

LSM trees dramatically reduce write amplification and improve throughput on write‑intensive workloads, making them the engine of choice for modern databases.

May 14, 2026 · 5 min · 898 words · martinuke0
Diagram comparing LSM tree layers with B‑tree nodes.

Why Log-Structured Merge Trees Outperform B-Trees for Write Throughput

Explore how LSM trees boost write performance compared to B‑trees, the mechanics behind their design, and the trade‑offs involved.

May 14, 2026 · 7 min · 1447 words · martinuke0
Diagram comparing LSM and B‑Tree write paths

Why LSM Trees Outperform B-Trees for Write‑Intense Workloads

An in‑depth comparison of LSM trees and B‑trees that explains why LSM excels on write‑heavy workloads, backed by real‑world examples and practical takeaways.

May 14, 2026 · 5 min · 1060 words · martinuke0
Diagram of a B‑tree node being split with copy‑on‑write semantics.

Why Copy-on-Write B-Trees Improve Database Concurrency Performance

This article explains how copy‑on‑write (COW) B‑trees work, why they improve concurrency, and what trade‑offs they introduce for modern database engines.

May 14, 2026 · 9 min · 1712 words · martinuke0
Diagram of a B-tree node being duplicated for copy‑on‑write.

How Copy-on-Write B-Trees Enable Instant Database Snapshots

Copy‑on‑write B‑trees let databases take point‑in‑time snapshots instantly, without blocking writes. This post explains the mechanics, trade‑offs, and real‑world implementations.

May 13, 2026 · 8 min · 1573 words · martinuke0
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