Understanding Kevo: A Lightweight LSM Tree Storage Engine in Go

Introduction

In the world of databases, storage engines play a critical role as the foundation that manages how data is stored, retrieved, and maintained. They ensure that data remains accessible and intact, even under heavy use. One such storage engine is Kevo, a lightweight and minimalist solution written in the Go programming language. Kevo is built on the Log-Structured Merge (LSM) tree architecture, designed to be both simple and effective. It provides the essential components needed to create more complex database systems, making it a valuable tool for developers and learners alike. In this article, we’ll explore what Kevo is, its features, how it works, and how you can use it in your projects.

What is Kevo?

Kevo is a storage engine that uses an LSM tree structure to manage data efficiently. A storage engine is like the backbone of a database—it handles the low-level tasks of storing data on disk, retrieving it when needed, and keeping everything organized. The LSM tree approach is particularly good at handling large amounts of data, especially when there are frequent write operations. It breaks data into smaller, manageable pieces, which are then merged over time to keep the system running smoothly.

Written in Go—a language known for its straightforward syntax and strong performance—Kevo is designed to be clean and easy to understand. Its simplicity makes it not only a practical choice for real-world applications but also an excellent way to learn about how storage engines function behind the scenes.

Key Features of Kevo

Kevo comes with a set of features that make it both powerful and flexible. Let’s break them down:

1. Single-Writer Architecture

Kevo allows only one process to write to the database at a time. This design choice keeps things simple by avoiding the complications that can arise when multiple writers try to update the data simultaneously. It reduces the risk of errors and makes the system easier to manage.

2. Complete Storage Primitives

Kevo includes all the core components of an LSM tree storage engine:

  • Write-Ahead Log (WAL): This acts like a safety net. Before any data is saved to the main storage, it’s recorded in the WAL. If something goes wrong—like a power failure—the WAL ensures that no data is lost.
  • MemTable: This is a temporary holding area in memory where recent data writes are kept. It uses a structure called a skiplist, which makes adding and finding data fast.
  • SSTables: These are files on disk where data is stored permanently. Once written, SSTables don’t change, which simplifies how Kevo manages them.
  • Compaction: Over time, Kevo merges SSTables to remove redundant data and keep storage efficient. This process happens in the background so it doesn’t interrupt normal use.

3. Configurable Durability

With Kevo, you can decide how often data is saved to disk. You can choose to save it after every write for maximum safety, or batch the saves for better speed. This flexibility lets you tune Kevo based on what matters most—data security or performance.

4. Composable Interfaces

Kevo provides simple building blocks for common tasks like reading data, writing data, browsing through it, and grouping operations into transactions. These interfaces make it easy for developers to customize Kevo or add it to larger systems.

5. ACID-Compliant Transactions

Transactions in Kevo follow the ACID rules—Atomicity, Consistency, Isolation, and Durability. This means that when you make changes to the database, they’re either fully completed or not applied at all, keeping your data reliable. Kevo uses a method inspired by SQLite to manage multiple readers and one writer at a time.

Where Can Kevo Be Used?

Kevo’s design makes it suitable for several practical scenarios. Here are some of its main use cases:

  • Educational Tool: If you’re curious about how storage engines work, Kevo’s clear and simple code is a great starting point. It’s like a textbook example brought to life.
  • Embedded Storage: For applications that need to store data locally—like a desktop app or a small device—Kevo offers a lightweight solution without the complexity of a full database.
  • Prototyping New Databases: Developers can use Kevo as a foundation to test new ideas for database systems, thanks to its modular design.
  • Go Applications: Since it’s written in Go, Kevo fits naturally into projects built with this language, providing a reusable storage option.

Getting Started with Kevo

Ready to try Kevo? Here’s how you can set it up and start using it.

Installation

Since Kevo is a Go package, you can add it to your project with a single command:

go get github.com/jeremytregunna/kevo

This downloads Kevo and makes it available for your Go programs.

Basic Usage

Here’s a simple example of how to use Kevo in a Go program:

package main

import (
    "fmt"
    "log"

    "github.com/jeremytregunna/kevo/pkg/engine"
)

func main() {
    // Open or create a storage engine at a given path
    eng, err := engine.NewEngine("/path/to/data")
    if err != nil {
        log.Fatalf("Failed to open engine: %v", err)
    }
    defer eng.Close()

    // Save a key-value pair
    if err := eng.Put([]byte("hello"), []byte("world")); err != nil {
        log.Fatalf("Failed to put: %v", err)
    }

    // Get a value using its key
    value, err := eng.Get([]byte("hello"))
    if err != nil {
        log.Fatalf("Failed to get: %v", err)
    }
    fmt.Printf("Value: %s\n", value)

    // Start a transaction
    tx, err := eng.BeginTransaction(false) // false means read-write
    if err != nil {
        log.Fatalf("Failed to start transaction: %v", err)
    }

    // Add data in the transaction
    if err := tx.Put([]byte("foo"), []byte("bar")); err != nil {
        tx.Rollback()
        log.Fatalf("Failed to put in transaction: %v", err)
    }

    // Save the transaction
    if err := tx.Commit(); err != nil {
        log.Fatalf("Failed to commit: %v", err)
    }

    // List all key-value pairs
    iter, err := eng.GetIterator()
    if err != nil {
        log.Fatalf("Failed to get iterator: %v", err)
    }

    for iter.SeekToFirst(); iter.Valid(); iter.Next() {
        fmt.Printf("%s: %s\n", iter.Key(), iter.Value())
    }
}

This code does a few things: it sets up a storage engine, saves a “hello-world” pair, retrieves it, uses a transaction to add another pair, and then lists all the data. It’s a quick way to see Kevo in action.

Exploring with the CLI Tool

Kevo also comes with a command-line tool that lets you interact with your database directly. To use it, run:

go run ./cmd/kevo/main.go /path/to/data

This creates a database at the path you specify (e.g., /tmp/foo.db becomes a directory holding your data). Once the tool is running, you can type commands like these:

kevo> PUT user:1 {"name":"John","email":"john@example.com"}
Value stored

kevo> GET user:1
{"name":"John","email":"john@example.com"}

kevo> BEGIN TRANSACTION
Started read-write transaction

kevo> PUT user:2 {"name":"Jane","email":"jane@example.com"}
Value stored in transaction (will be visible after commit)

kevo> COMMIT
Transaction committed (0.53 ms)

kevo> SCAN user:
user:1: {"name":"John","email":"john@example.com"}
user:2: {"name":"Jane","email":"jane@example.com"}
2 entries found

Type .help in the CLI to see all available commands. This tool is a handy way to test Kevo without writing code.

Customizing Kevo with Configuration

Kevo lets you adjust its settings to match your needs. For example, you might want to optimize it for lots of writes. Here’s how you can create a custom setup:

config := config.NewDefaultConfig(dbPath)
config.MemTableSize = 64 * 1024 * 1024  // Set MemTable to 64MB
config.WALSyncMode = config.SyncBatch   // Batch disk saves for speed
config.SSTableBlockSize = 32 * 1024     // Use 32KB blocks

eng, err := engine.NewEngineWithConfig(config)

These options control things like how much data is held in memory before being written to disk, how often the disk is updated, and how data is organized in files. You can tweak them to prioritize speed, safety, or storage space, depending on your project.

How Kevo Works: The Architecture

To really understand Kevo, it helps to look at its building blocks. Here’s a breakdown of its LSM tree architecture:

  • Write-Ahead Log (WAL): Every change is logged here first. It’s like a journal that keeps your data safe in case of a crash.
  • MemTable: This holds new data in memory using a skiplist. It’s fast because it doesn’t touch the disk yet.
  • SSTables: When the MemTable fills up, its data is saved to disk as an SSTable. These files are fixed once created, which keeps things simple.
  • Compaction: As SSTables pile up, Kevo combines them to save space and speed up reads. This happens automatically in the background.
  • Transactions: Kevo groups operations into transactions that follow ACID rules, ensuring your data stays consistent.

These pieces work together to balance speed and reliability. The WAL and MemTable make writes quick, SSTables store data long-term, compaction keeps things tidy, and transactions protect your work.

Testing Kevo’s Performance

Want to see how fast Kevo is? It includes a tool called storage-bench for running performance tests:

go run ./cmd/storage-bench/... -type=all

This command runs a full set of benchmarks. You can check the tool’s README file for more options. It’s a good way to measure how Kevo handles your specific workload.

What Kevo Isn’t Designed For

Kevo has a clear focus, and there are some things it doesn’t aim to do:

  • It’s not trying to match the features of bigger storage engines like RocksDB or LevelDB.
  • It’s built for a single computer, not for spreading data across multiple machines.
  • It doesn’t handle complex queries—that’s left to other tools you might build on top of it.

Knowing these limits helps you decide if Kevo fits your needs.

Building and Testing Kevo Yourself

If you want to dig deeper, you can build and test Kevo on your own machine:

# Build everything
go build ./...

# Run tests
go test ./...

# Run benchmarks
go test ./pkg/path/to/package -bench .

These commands compile the code, check that it works, and measure its performance. If you’d like to improve Kevo, you’re welcome to submit changes via a Pull Request.

License Information

Kevo is free to use under the Apache License, Version 2.0. This means you can use it, modify it, and share it, as long as you follow the license rules. You can find the full details at https://www.apache.org/licenses/LICENSE-2.0.

Wrapping Up

Kevo shows how a simple design can still be powerful. By focusing on the essentials—an LSM tree structure, a clean Go implementation, and flexible options—it serves as both a practical tool and a learning resource. Whether you’re building an app that needs local storage, testing a new database idea, or studying storage engines, Kevo offers a solid starting point.

Its straightforward approach, combined with features like ACID transactions and customizable settings, makes it a reliable choice for managing data. As Go continues to grow in popularity, tools like Kevo provide a native way to handle storage needs efficiently. If you’re looking for a lightweight, dependable storage engine, Kevo is worth a closer look.