Pros of RocksDB

• Mature and widely adopted in production environments
• Extensive documentation and community support
• Offers a wide range of features, including column families and transactions

Cons of RocksDB

• Higher memory usage compared to FASTER
• Can be slower for certain workloads, especially those involving large key-value pairs
• More complex configuration and tuning required for optimal performance

Code Comparison

RocksDB:

rocksdb::DB* db;
rocksdb::Options options;
options.create_if_missing = true;
rocksdb::Status status = rocksdb::DB::Open(options, "/path/to/db", &db);
db->Put(rocksdb::WriteOptions(), "key", "value");

FASTER:

var store = new FasterKV<Key, Value>(1L << 20, new LogSettings { ... });
var session = store.NewSession();
session.Upsert(key, value);

Key Differences

• FASTER is designed for low-latency, high-throughput scenarios, while RocksDB focuses on general-purpose key-value storage
• FASTER uses a novel hybrid log-structured architecture, whereas RocksDB is based on a Log-Structured Merge-Tree (LSM)
• RocksDB provides more advanced features like snapshots and column families, while FASTER emphasizes simplicity and performance
• FASTER is primarily designed for .NET environments, while RocksDB has broader language support

Pros of FoundationDB

• Distributed architecture with strong ACID guarantees
• Multi-model database supporting key-value, document, and relational models
• Scalable to handle large datasets across multiple machines

Cons of FoundationDB

• Steeper learning curve due to its distributed nature
• Limited language support compared to FASTER
• May have higher operational complexity for small-scale applications

Code Comparison

FoundationDB (Python):

@fdb.transactional
def add_user(tr, user_id, name):
    tr[f'users:{user_id}:name'] = name

db = fdb.open()
add_user(db, '123', 'John Doe')

FASTER (C#):

using var session = store.NewSession();
session.Upsert(key, value);
session.Refresh();

Key Differences

• FoundationDB focuses on distributed systems, while FASTER is designed for single-node performance
• FASTER provides lower-level control over data structures and memory management
• FoundationDB offers stronger consistency guarantees in a distributed environment
• FASTER is more suitable for embedded scenarios and high-performance local operations

Both projects have their strengths, with FoundationDB excelling in distributed environments and FASTER optimized for single-node performance and flexibility.

Pros of Pebble

• Designed specifically for key-value storage, optimized for SSDs
• Better support for concurrent reads and writes
• More mature and battle-tested in production environments

Cons of Pebble

• Less flexible than FASTER for different data structures
• May have higher memory usage in certain scenarios
• Limited to Go language, while FASTER supports multiple languages

Code Comparison

Pebble (Go):

db, err := pebble.Open("path/to/db", &pebble.Options{})
if err != nil {
    log.Fatal(err)
}
defer db.Close()

FASTER (C#):

var log = Devices.CreateLogDevice("path/to/log");
var store = new FasterKV<Key, Value>(1L << 20, new LogSettings { LogDevice = log });

Both libraries provide simple APIs for opening and interacting with key-value stores, but FASTER offers more flexibility in terms of data types and storage options. Pebble's API is more focused on traditional key-value operations, while FASTER allows for custom data structures and indexing schemes.

Pebble is tailored for use in distributed systems like CockroachDB, offering strong consistency guarantees. FASTER, on the other hand, provides a broader set of features for various use cases, including in-memory operations and hybrid log-based storage.

Pros of LevelDB

• Mature and widely adopted key-value store with a proven track record
• Simple and lightweight API, easy to integrate into existing projects
• Supports ordered iteration over keys, useful for range queries

Cons of LevelDB

• Limited concurrency support, primarily designed for single-threaded access
• Lacks built-in support for complex data structures or advanced indexing
• Performance can degrade with large datasets due to compaction overhead

Code Comparison

LevelDB:

leveldb::DB* db;
leveldb::Options options;
options.create_if_missing = true;
leveldb::Status status = leveldb::DB::Open(options, "/tmp/testdb", &db);
db->Put(leveldb::WriteOptions(), "key", "value");

FASTER:

var store = new FasterKV<Key, Value>(1L << 20, new LogSettings { LogDevice = device });
var session = store.NewSession();
session.Upsert(key, value);

FASTER offers a more flexible API with support for concurrent operations and custom key-value types, while LevelDB provides a simpler interface focused on basic key-value operations. FASTER's design allows for better scalability and performance in multi-threaded scenarios, whereas LevelDB excels in simplicity and ease of use for single-threaded applications.