CouchDB vs BigMemory

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

CouchDB is a Development solution with tags like nosql, json, documentoriented, scalable.

It boasts features such as Document oriented database, JSON document storage, JavaScript as query language, MapReduce for aggregation, Master-master replication, RESTful API and pros including High availability, Easy horizontal scalability, Schema-less, JSON data model, Powerful query capabilities.

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.

CouchDB

CouchDB

CouchDB is an open-source NoSQL document-oriented database that focuses on ease of use and scalability. It uses JSON documents and JavaScript as its query language, allowing you to store, access, and manage data in a simple yet flexible way.

Categories:
Development Databases
nosql json documentoriented scalable

CouchDB Features

  1. Document oriented database
  2. JSON document storage
  3. JavaScript as query language
  4. MapReduce for aggregation
  5. Master-master replication
  6. RESTful API

Pricing

  • Open Source

Pros

High availability

Easy horizontal scalability

Schema-less

JSON data model

Powerful query capabilities

Cons

Not suitable for complex transactions

Limited query flexibility compared to SQL

Steep learning curve

BigMemory

BigMemory

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.

Categories:
Development In-Memory Databases
caching data-management low-latency

BigMemory Features

  1. Distributed in-memory data storage
  2. Automatic data eviction and loading
  3. Read/write caching for databases
  4. Support for terabytes of data
  5. Integration with Hadoop and Spark
  6. High availability through replication and failover

Pricing

  • Subscription-Based

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