BigMemory vs memcached

Struggling to choose between BigMemory and memcached? Both products offer unique advantages, making it a tough decision.

BigMemory is a Development solution with tags like caching, data-management, low-latency.

It boasts features such as 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 and pros including 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.

On the other hand, memcached is a Network & Admin product tagged with caching, memory, performance.

Its standout features include In-memory key-value store, Distributed architecture, Simple protocol, Horizontal scalability, and it shines with pros like 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

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

• Subscription-Based

memcached

• Open Source