RAMCloud

RAMCloud is a distributed in-memory storage system designed for low-latency and high-throughput applications. It provides persistent storage with sub-microsecond access times by keeping all data in DRAM while ensuring durability through fast logging to disk or flash.

1 Overview

RAMCloud aims to combine:

• Low-Latency Storage: Data is stored entirely in DRAM for rapid access.
• High Availability: Data is replicated across servers for fault tolerance.
• Durability: Uses fast disk/flash logging to prevent data loss.
• Scalability: Can scale to thousands of nodes while maintaining low-latency access.

RAMCloud is particularly useful in environments requiring real-time data access, such as financial systems, search engines, and large-scale web applications.

2 Key Features

• Sub-Microsecond Latency: Provides faster access than traditional disk-based storage.
• Distributed Key-Value Store: Supports efficient data retrieval across a cluster.
• Crash Recovery in Seconds: Recovers lost data quickly by reloading from logs.
• High Scalability: Designed to handle petabyte-scale datasets with thousands of servers.

3 How RAMCloud Works

1. Data Storage in DRAM: All active data is stored in memory for fast retrieval.
2. Log-Structured Storage: Updates are written sequentially to persistent logs.
3. Crash Recovery Mechanism: Lost data is restored by replaying logs across servers.
4. Distributed Coordination: A master node manages metadata, while worker nodes handle data storage.

Example Usage

RAMCloud supports a key-value API that allows fast reads and writes:

// Connect to a RAMCloud cluster
RAMCloud::Client client("tcp:host=ramcloud-cluster");

// Store a key-value pair
client.write("myTable", "key1", "Hello RAMCloud!");

// Retrieve a value
string value;
client.read("myTable", "key1", &value);
cout << "Retrieved: " << value << endl;

Comparison with Other Storage Systems

Feature	RAMCloud	Redis	Apache Cassandra
Storage Medium	DRAM (with disk backup)	DRAM	Disk
Primary Use Case	Low-latency storage	Caching	Distributed database
Replication	Log-based persistence	In-memory replication	Multi-node replication
Fault Tolerance	Fast recovery via logs	Data loss risk without persistence	High availability with replication

Advantages

• Provides ultra-low-latency storage.
• Recovers from crashes within seconds.
• Scales efficiently across large distributed clusters.

Limitations

• Requires large amounts of DRAM, making it expensive.
• Not suitable for workloads requiring deep historical storage.
• Limited adoption compared to more established distributed databases.

Applications

• Real-Time Analytics: Used in financial trading and fraud detection.
• Search Engine Indexing: Supports rapid access to large indexes.
• Web Applications: Reduces response times for latency-sensitive services.
• Machine Learning Serving: Stores feature embeddings for fast model inference.

See Also

• In-Memory Computing
• Distributed Storage
• Redis
• Apache Cassandra
• Key-Value Store
• High-Performance Computing