fjall
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🗻 LSM-based embeddable key-value storage engine written in safe Rust
Fjall is an LSM-based embedded 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, 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()?;
// 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
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.