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Open-Source Databases · skyzh

mini-lsm

Mini-LSM is an educational Rust project that teaches how to build a Log-Structured Merge (LSM) tree storage engine—the foundation of modern key-value databases. It provides a structured three-week course with starter code, reference solutions, and hands-on exercises covering storage format, compaction, persistence, and multi-version concurrency control.

Source: GitHub — github.com/skyzh/mini-lsm
4k
GitHub stars
616
Forks
Rust
Primary language
Apache-2.0
License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

FieldValue
Repositoryskyzh/mini-lsm
Ownerskyzh
Primary languageRust
LicenseApache-2.0 — OSI-approved
Stars4k
Forks616
Open issues26
Latest releasev202501 (2025-01-20)
Last updated2026-04-22
Sourcehttps://github.com/skyzh/mini-lsm

What mini-lsm is

A Rust-based educational framework implementing an LSM-tree database engine, covering memtables, sorted string tables (SSTs), block encoding, compaction strategies (leveled, tiered, simple), write-ahead logs (WAL), manifests, and MVCC with optimistic concurrency control. Includes reference implementations, a CLI tool, and a compaction simulator for experimentation.

Quickstart

Get the mini-lsm source

Clone the repository and explore it locally.

terminalbash
git clone https://github.com/skyzh/mini-lsm.gitcd mini-lsm# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

Learning LSM-tree fundamentals

Ideal for engineers and students who need to understand how modern key-value stores (RocksDB, LevelDB, Cassandra) work internally. The structured three-week course with daily chapters makes it accessible.

Building custom storage engines

Provides a foundation and reference implementation for teams designing specialized storage systems, especially those needing object-storage backends or embedded databases in Rust.

Prototyping and research

Well-suited for experimenting with compaction strategies, concurrency models, and storage optimizations before production implementation. The compaction simulator and modular design support rapid iteration.

Implementation considerations

  • Completion requires active coding through three weeks of structured lessons; expect 20–40 hours of hands-on work depending on prior Rust and systems knowledge.
  • Course structure is linear (weeks 1→2→3); skipping chapters is difficult. Ensure team alignment on learning timeline before starting.
  • Reference solutions are available in separate directories (mini-lsm and mini-lsm-mvcc); use for comparison, not as shortcuts. Cargo custom commands (cargo x copy-test, cargo x sync) streamline development.
  • The starter crate (mini-lsm-starter) is the primary entry point for learners; reference implementations should be consulted only after attempting exercises.
  • Compaction simulator tool is valuable for testing custom compaction algorithms before integration into the main engine.

When to avoid it — and what to weigh

  • Production storage engine needed immediately — This is a teaching project, not a hardened production database. It lacks maturity, extensive performance tuning, and real-world operational tooling. Use RocksDB, LevelDB, or similar instead.
  • No time for deep understanding — Requires reading course materials and implementing solutions week-by-week. Not a copy-paste library; completion demands active learning and coding effort.
  • Strict compatibility and SLA requirements — As an educational codebase, breaking changes and experimental features may appear. Not guaranteed to maintain backward compatibility or API stability.
  • Multi-language or polyglot ecosystem needed — Rust-only implementation. If your stack requires Java, Go, or other languages, you'll need separate implementations or language bindings.

License & commercial use

Apache License 2.0 (Apache-2.0). Permissive OSI-approved license allowing commercial use, modification, and distribution with attribution and liability disclaimer. Course materials (markdown, figures) are reserved by the author; code is licensed under Apache 2.0.

Apache 2.0 is a permissive OSI license that allows commercial use without royalties. You may build proprietary systems using this code as a foundation, but you must retain the license notice and disclaimer. The author reserves copyright to course materials (docs/figures), not the code itself. For production deployment, treat this as a learning reference, not a drop-in database library, and ensure your security and performance validation is independent.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

SignalAssessment
MaintenanceActive
DocumentationStrong
License clarityClear
Deployment complexityLow
DEV.co fitGood
Assessment confidenceHigh
Security considerations

Not a production-hardened database. Security is not a primary design concern for an educational project. No claims made regarding cryptography, authentication, access control, or protection against side-channel attacks. If you deploy code derived from mini-lsm, conduct independent security review: consider data encryption at rest, integrity checks (checksums are implemented), fuzzing, and audit logging. The project implements checksums and basic validation (week 2.7 on batch writes), but does not address network security, privilege isolation, or compliance (GDPR, HIPAA, etc.).

Alternatives to consider

RocksDB

Production-grade LSM-tree engine in C++, with bindings for Rust and other languages. Mature, battle-tested, high performance. Use if you need a real database now; RocksDB's source is also instructive but less pedagogical.

LevelDB

Simpler LSM implementation in C++, easier to read than RocksDB but still not a tutorial. Useful if you want to study a production system's internals without committing to a course.

Prost or other Rust data-structure libraries

If you only need a key-value store without building one from scratch, libraries like sled or dashmap offer simpler off-the-shelf solutions; mini-lsm is for understanding, not convenience.

Software development agency

Build on mini-lsm with DEV.co software developers

Join the mini-lsm community and complete the three-week course. Study the book, implement the exercises, and compare with reference solutions. Perfect for systems engineers and database developers who want hands-on understanding of modern key-value stores.

Talk to DEV.co

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mini-lsm FAQ

Can I use mini-lsm in production?
Not recommended. Mini-LSM is explicitly an educational tool. Use RocksDB, LevelDB, or similar for production. You may study mini-lsm's code to understand LSM design, then build a custom engine if needed, but mini-lsm itself is not hardened for production workloads.
How long does the course take?
Officially three weeks, with seven daily chapters per week. Actual time depends on your Rust and systems background; expect 20–40 hours of active coding and reading.
Do I need prior database experience?
No, but familiarity with Rust and basic data structures (trees, hash maps) is assumed. The course teaches LSM concepts from first principles.
Is the code performant?
Mini-LSM prioritizes clarity over performance. The reference implementation is not benchmarked against production systems. If performance is critical, profile and optimize; the modular design supports experimentation.

Software development & web development with DEV.co

Adopting mini-lsm is usually one piece of a larger software development effort. As a software development agency, DEV.co provides software development services and web development expertise — pairing senior software developers and web developers with your team to design, build, and operate open-source databases software in production.

Ready to Master LSM Storage Engines?

Join the mini-lsm community and complete the three-week course. Study the book, implement the exercises, and compare with reference solutions. Perfect for systems engineers and database developers who want hands-on understanding of modern key-value stores.