BigMemory vs MongoDB

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.

BigMemory icon
BigMemory
MongoDB icon
MongoDB

Expert Analysis & Comparison

Struggling to choose between BigMemory and MongoDB? 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, MongoDB is a Development product tagged with nosql, document-database, open-source.

Its standout features include Document-oriented storage, Automatic sharding, Rich and expressive query language, High availability, Horizontal scalability, and it shines with pros like Flexible schema, High performance, Easy scalability, Rich query capabilities, High availability.

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 BigMemory and MongoDB?

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

Market Position & Industry Recognition

BigMemory and MongoDB have established themselves in the development market. Key areas include caching, data-management, low-latency.

Technical Architecture & Implementation

The architectural differences between BigMemory and MongoDB significantly impact implementation and maintenance approaches. Related technologies include caching, data-management, low-latency.

Integration & Ecosystem

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

Decision Framework

Consider your technical requirements, team expertise, and integration needs when choosing between BigMemory and MongoDB. You might also explore caching, data-management, low-latency for alternative approaches.

Feature BigMemory MongoDB
Overall Score N/A 1
Primary Category Development 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

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: Open Source Test Automation Framework

Founded: 2011

Primary Use: Mobile app testing automation

Supported Platforms: iOS, Android, Windows

MongoDB
MongoDB

Description: MongoDB is a popular open-source, document-oriented NoSQL database. It stores data in flexible, JSON-like documents, rather than rows and columns used in traditional RDBMS. MongoDB is scalable, high-performance and easy to use.

Type: Cloud-based Test Automation Platform

Founded: 2015

Primary Use: Web, mobile, and API testing

Supported Platforms: Web, iOS, Android, API

Key Features Comparison

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
MongoDB
MongoDB Features
  • Document-oriented storage
  • Automatic sharding
  • Rich and expressive query language
  • High availability
  • Horizontal scalability

Pros & Cons Analysis

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
MongoDB
MongoDB
Pros
  • Flexible schema
  • High performance
  • Easy scalability
  • Rich query capabilities
  • High availability
Cons
  • No transactions
  • No joins
  • Limited query flexibility compared to SQL
  • Steep learning curve

Pricing Comparison

BigMemory
BigMemory
  • Subscription-Based
MongoDB
MongoDB
  • Open Source
  • Subscription-Based

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