moss
A simple, fast, ordered, persistable key-value storage library for Go, using an LSM-like design.
What is moss?
Moss is a Go library that provides a simple, fast, and ordered key-value storage implementation with persistence. It solves the need for an efficient, concurrent, and persistable key-value collection within Go applications, using an LSM-like design with immutable sorted segments.
Go developers building applications that require embedded key-value storage with ordered data, concurrent access, and persistence, such as databases, caching layers, or state management systems.
Developers choose Moss for its pure Go implementation, non-blocking concurrent reads and writes, efficient snapshot isolation, and flexible persistence options, making it a lightweight yet powerful alternative to heavier storage engines.
Overview
moss - a simple, fast, ordered, persistable, key-val storage library for golang
Use Cases
Best For
- Embedding a persistent key-value store in Go applications
- Implementing concurrent data structures with snapshot support
- Building lightweight databases or storage layers
- Handling write-heavy workloads with merge operations
- Creating ordered collections with range iteration
- Developing educational or experimental storage systems
Not Ideal For
- Applications requiring complex query languages or SQL-like interfaces beyond key-value lookups
- Distributed systems needing built-in replication or clustering out of the box
- Use cases where batch operations frequently include duplicate keys, violating Moss's uniqueness constraint
- Handling values larger than 268MB due to internal length encoding limitations
Pros & Cons
Pros
Readers and writers operate independently without locks, enabling high throughput in concurrent environments as per the immutable segment stack design.
Snapshots provide consistent reads with low overhead by cloning the segment stack, ideal for transactional views without blocking writes.
Merge operations allow efficient handling of write-heavy workloads like counters, reducing I/O overhead through read-compute-write optimizations.
mossStore offers append-only writes and memory-mapped reads with configurable compaction, and hooks allow integration with external storage like LevelDB or SQLite.
Cons
Each batch must have unique keys, forcing applications to manage this constraint externally, which can complicate logic for some use cases.
Performance relies on background merger tasks; if slow or misconfigured, it can stall ingest of new batches, requiring careful tuning of CollectionOptions.
Long-lived snapshots or iterators can delay reclamation of old segments, potentially leading to increased memory usage and performance degradation.
Frequently Asked Questions
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