BigMemory vs memcached

BigMemory — BigMemory is an in-memory data management system that provides a fast, scalable cache and data store for applications. It allows storing terabytes of data in memory for low-latency data access.

memcached — Memcached is an open source, high-performance distributed memory object caching system. It is used to speed up dynamic web applications by alleviating database load for reading/writing frequently acce

BigMemory offers Distributed in-memory data storage, Automatic data eviction and loading, Read/write caching for databases, Support for terabytes of data, Integration with Hadoop and Spark, while memcached provides In-memory key-value store, Distributed architecture, Simple protocol, Horizontal scalability.

BigMemory stands out for Very fast data access and throughput, Reduces load on databases, Scales horizontally; memcached is known for Very fast data lookup, Reduces database load, Improves overall application performance.

Feature	BigMemory	memcached
Overall Score	N/A	N/A
Primary Category	Development	Network & Admin
Pricing	N/A	Open Source

Product Overview

BigMemory

Description: BigMemory is an in-memory data management system that provides a fast, scalable cache and data store for applications. It allows storing terabytes of data in memory for low-latency data access.

memcached

Description: Memcached is an open source, high-performance distributed memory object caching system. It is used to speed up dynamic web applications by alleviating database load for reading/writing frequently accessed data.

Key Features Comparison

BigMemory Features

• Distributed in-memory data storage
• Automatic data eviction and loading
• Read/write caching for databases
• Support for terabytes of data
• Integration with Hadoop and Spark
• High availability through replication and failover

memcached Features

• In-memory key-value store
• Distributed architecture
• Simple protocol
• Horizontal scalability

Pros & Cons Analysis

BigMemory

Pros

• Very fast data access and throughput
• Reduces load on databases
• Scales horizontally
• Lowers infrastructure costs by using RAM instead of disks
• Supports both Java and .NET platforms

Cons

• Can lose data if not persisted
• RAM is more expensive than disk
• Not fully ACID compliant
• Can be complex to configure and tune

memcached

Pros

• Very fast data lookup
• Reduces database load
• Improves overall application performance

Cons

• Data loss on server restart
• Additional system complexity
• Requires application code changes

Pricing Comparison

BigMemory

• Not listed

memcached

• Open Source