DharmaDB

DharmaDB is a persistent, fault tolerant Key-Value Store written in Rust.

Setup

Just create an instance of Dharma to get the key value store up and running. ```rust use dharmadb::dharma::Dharma; use dharmadb::errors::Errors; use dharmadb::options::DharmaOpts;

// configure options such as database persistence path // or block size using DharmaOpts or use the defaults let options = DharmaOpts::default(); let db_result: Result = Dharma::new(options);

// start using database let db = db_result.unwrap(); ```

Operations

DharmaDB supports a native Rust API and supports common operations of a key/value store.

The API allows you to store generic Key Value pairs using the Dharma<K, V> interface.

put

The put operation is used to persist a value associated with a key to the store. ```rust use dharmadb::dharma::Dharma; use dharmadb::errors::Errors; use dharmadb::options::DharmaOpts;

let options = DharmaOpts::default(); let db_result: Result, Errors> = Dharma::new(options);

// persist key / value pair let putresult = db.put(mykey, my_value); ```

get

The get operation retrieves the value associated with a key if it exists. ```rust use dharmadb::dharma::Dharma; use dharmadb::errors::Errors; use dharmadb::options::DharmaOpts;

let options = DharmaOpts::default(); let db_result: Result, Errors> = Dharma::new(options);

// get the key if it exists let getresult = db.get(&mykey); let maybevalue: Option = getresult.unwrap(); ```

recover

The recover operation is required in cases of unexpected crashes. Generally, Dharma will detect non-graceful exit and suggest running recovery on startup. ```rust use dharmadb::dharma::Dharma; use dharmadb::errors::Errors; use dharmadb::options::DharmaOpts;

let options = DharmaOpts::default(); // try recovering data after non-graceful shutdown by calling recover let recovereddbresult = Dharma::::recover(options); ```

Features

• Store arbitrary key/value pairs.
• Data is sorted by key to ensure fast reads.
• Store Custom Data types using the Generic Interface.
• Sort order of data can be configured by implementing Ord trait for your data type.
• Fault Tolerant store with option for recovery in case of failure.

DharmaDB does not provide client-server communication. Applications can wrap DharmaDB with a server to enable API access.

Performance

Benchmarking is in a very nascent stage still. Benchmarks have been added for get and put operations in the benches directory. Benchmarks were carried out on a macbook with the following configuration.

Results are summarized below. markdown Model Name: MacBook Air Model Identifier: MacBookAir10,1 Chip: Apple M1 Total Number of Cores: 8 (4 performance and 4 efficiency) Memory: 8 GB

The performance numbers were gerated using the Criterion.rs package.

Performance was gauged by filling a database with a thousand initial values and then flushing to disk to force sstable creation. The benchmark scripts in benches folder were executed on this database. markdown put operation time: 70.656 ms per operation get operation time: 17.570 us per operation

Contributing

Contributions to DharmaDB are welcome. For more complex PRs please raise an issue outlining the problem / enhancement and how you intend to solve it. All PRs should be accompanied with tests. The docs folder contains an assortment of files that detail the inner workings of DharmaDB. The tests folder also reveals a lot about the inner workings of the database. You can start off by reading DharmaDB Design