Fjall is an LSM-based embeddable key-value storage engine written in Rust. It features:

• Thread-safe BTreeMap-like API
• 100% safe & stable Rust
• Range & prefix searching with forward and reverse iteration
• Cross-partition snapshots (MVCC)
• Automatic background maintenance

Each Keyspace is a single logical database and is split into partitions (a.k.a. column families) - you should probably only use a single keyspace for your application. Each partition is physically a single LSM-tree and its own logical collection; however, write operations across partitions are atomic as they are persisted in a single database-level journal, which will be recovered on restart.

It is not:

• a standalone server
• a relational database
• a wide-column database: it has no notion of columns

Keys are limited to 65536 bytes, values are limited to 2^32 bytes. As is normal with any kind of storage engine, larger keys and values have a bigger performance impact.

For the underlying LSM-tree implementation, see: https://crates.io/crates/lsm-tree.

Basic usage

cargo add fjall

use fjall::{Config, FlushMode, Keyspace, PartitionCreateOptions};

let keyspace = Config::new(folder).open()?;

// Each partition is its own physical LSM-tree
let items = keyspace.open_partition("my_items", PartitionCreateOptions::default())?;

// Write some data
items.insert("a", "hello")?;

// And retrieve it
let bytes = items.get("a")?;

// Or remove it again
items.remove("a")?;

// Search by prefix
for item in &items.prefix("prefix") {
  // ...
}

// Search by range
for item in &items.range("a"..="z") {
  // ...
}

// Iterators implement DoubleEndedIterator, so you can search backwards, too!
for item in items.prefix("prefix").into_iter().rev() {
  // ...
}

// Atomic write batches (multiple partitions can be used in a single batch)
let mut batch = keyspace.batch();
batch.insert(&items, "1", "abc");
batch.insert(&items, "3", "abc");
batch.insert(&items, "5", "abc");
batch.commit()?;

// Sync the journal to disk to make sure data is definitely durable
// When the keyspace is dropped, it will try to persist
// Also, by default every second the keyspace will be persisted asynchronously
keyspace.persist(FlushMode::SyncAll)?;

// Destroy the partition, removing all data in it.
// This may be useful when using temporary tables or indexes,
// as it is essentially an O(1) operation.
keyspace.delete_partition(items)?;

Details

• Partitions (a.k.a. column families) with cross-partition atomic semantics (atomic write batches)
• Sharded journal for concurrent writes
• Cross-partition snapshots (MVCC)
• anything else implemented in lsm-tree

Durability

Fjall is agnostic about which type of durability needs your application needs to support different workloads. After writing data (be it, insert, remove or committing a write batch), you can choose to call Keyspace::persist which takes a FlushMode parameter.

Features

bloom

Uses bloom filters to reduce disk I/O for non-existing keys. Improves point read performance, but increases memory usage.

Disabled by default.

Stable disk format

The disk format will be stable from 1.0.0 (oh, the dreaded 1.0.0...) onwards. Any breaking change after that will result in a major bump.

Examples

See here for practical examples.

And checkout Smoltable, a standalone Bigtable-inspired mini wide-column database using fjall as its storage engine.

Contributing

How can you help?

• Ask a question
• Post benchmarks and things you created
• Open an issue (bug report, weirdness)
• Open a PR

License

All source code is licensed under MIT OR Apache-2.0.

All contributions are to be licensed as MIT OR Apache-2.0.