RethinkDB vs BigMemory

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

RethinkDB is a Development solution with tags like nosql, json, document-database, distributed, scalable, high-availability.

It boasts features such as Distributed JSON document database, Automatic sharding, Fault tolerance and automatic failover, High availability, Simple query language, Changefeeds for realtime queries, Strong consistency and pros including Horizontally scalable, High performance, Easy to use query language, Realtime push queries, Open source with permissive license.

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.

Feature	RethinkDB	BigMemory
Overall Score	N/A	N/A
Primary Category	Development	Development

Product Overview

RethinkDB

Description: RethinkDB is an open-source, distributed JSON document database that focuses on easy scalability and high availability. It has an intuitive query language and simple administration tools.

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.

Key Features Comparison

RethinkDB Features

• Distributed JSON document database
• Automatic sharding
• Fault tolerance and automatic failover
• High availability
• Simple query language
• Changefeeds for realtime queries
• Strong consistency

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

RethinkDB

Pros

• Horizontally scalable
• High performance
• Easy to use query language
• Realtime push queries
• Open source with permissive license

Cons

• Limited adoption and small community
• Development discontinued in 2016
• Fewer features than other NoSQL databases

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

RethinkDB

• Open Source

BigMemory

• Subscription-Based