memcached vs BigMemory

Professional comparison and analysis to help you choose the right software solution for your needs. Compare features, pricing, pros & cons, and make an informed decision.

memcached icon
memcached
BigMemory icon
BigMemory

Expert Analysis & Comparison

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

memcached is a Network & Admin solution with tags like caching, memory, performance.

It boasts features such as In-memory key-value store, Distributed architecture, Simple protocol, Horizontal scalability and pros including Very fast data lookup, Reduces database load, Improves overall application performance.

On the other hand, BigMemory is a Development product tagged with caching, data-management, low-latency.

Its standout features include 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 it shines with pros like 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.

To help you make an informed decision, we've compiled a comprehensive comparison of these two products, delving into their features, pros, cons, pricing, and more. Get ready to explore the nuances that set them apart and determine which one is the perfect fit for your requirements.

Why Compare memcached and BigMemory?

When evaluating memcached versus BigMemory, both solutions serve different needs within the network & admin ecosystem. This comparison helps determine which solution aligns with your specific requirements and technical approach.

Market Position & Industry Recognition

memcached and BigMemory have established themselves in the network & admin market. Key areas include caching, memory, performance.

Technical Architecture & Implementation

The architectural differences between memcached and BigMemory significantly impact implementation and maintenance approaches. Related technologies include caching, memory, performance.

Integration & Ecosystem

Both solutions integrate with various tools and platforms. Common integration points include caching, memory and caching, data-management.

Decision Framework

Consider your technical requirements, team expertise, and integration needs when choosing between memcached and BigMemory. You might also explore caching, memory, performance for alternative approaches.

Feature memcached BigMemory
Overall Score N/A N/A
Primary Category Network & Admin Development
Target Users Developers, QA Engineers QA Teams, Non-technical Users
Deployment Self-hosted, Cloud Cloud-based, SaaS
Learning Curve Moderate to Steep Easy to Moderate

Product Overview

memcached
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.

Type: Open Source Test Automation Framework

Founded: 2011

Primary Use: Mobile app testing automation

Supported Platforms: iOS, Android, Windows

BigMemory
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.

Type: Cloud-based Test Automation Platform

Founded: 2015

Primary Use: Web, mobile, and API testing

Supported Platforms: Web, iOS, Android, API

Key Features Comparison

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

Pros & Cons Analysis

memcached
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
BigMemory
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

Pricing Comparison

memcached
memcached
  • Open Source
BigMemory
BigMemory
  • Subscription-Based

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