ScaleOut vs memcached

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

ScaleOut is a Ai Tools & Services solution with tags like distributed-computing, inmemory-data, high-performance-computing, analytics, machine-learning.

It boasts features such as Distributed in-memory data grid, Real-time event processing, High-performance computing capabilities, Scales analytics and machine learning applications, Runs on commodity hardware and pros including Scales horizontally, Lowers costs by using commodity hardware, Accelerates analytics and ML applications, Provides real-time capabilities.

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.

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.

ScaleOut

ScaleOut

ScaleOut is a software platform designed to scale and accelerate analytics and machine learning applications across clusters of commodity computers. It provides distributed in-memory data grid, real-time event processing, and high-performance computing capabilities.

Categories:
distributed-computing inmemory-data high-performance-computing analytics machine-learning

ScaleOut Features

  1. Distributed in-memory data grid
  2. Real-time event processing
  3. High-performance computing capabilities
  4. Scales analytics and machine learning applications
  5. Runs on commodity hardware

Pricing

  • Subscription-Based
  • Pay-As-You-Go

Pros

Scales horizontally

Lowers costs by using commodity hardware

Accelerates analytics and ML applications

Provides real-time capabilities

Cons

Requires expertise to set up and manage clustering

May require code changes to distribute applications

Limited ecosystem compared to alternatives like Spark


memcached

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 accessed data.

Categories:
caching memory performance

Memcached Features

  1. In-memory key-value store
  2. Distributed architecture
  3. Simple protocol
  4. Horizontal scalability

Pricing

  • Open Source

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