OrbitDB vs BigMemory

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

OrbitDB is a Development solution with tags like decentralized, peertopeer, ipfs, distributed-web.

It boasts features such as Decentralized database, Built on IPFS, Event log for database changes, Supports CRUD operations, Access control lists, Queryable database API and pros including Decentralization provides censorship resistance, Data is distributed across nodes, Immutable append-only log, Fine-grained access control, Interoperable with other IPFS tools.

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	OrbitDB	BigMemory
Overall Score	N/A	N/A
Primary Category	Development	Development

Product Overview

OrbitDB

Description: OrbitDB is a decentralized peer-to-peer database that allows developers to build decentralized applications. It works on top of IPFS, providing an API for managing databases on the distributed web.

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

OrbitDB Features

• Decentralized database
• Built on IPFS
• Event log for database changes
• Supports CRUD operations
• Access control lists
• Queryable database API

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

OrbitDB

Pros

• Decentralization provides censorship resistance
• Data is distributed across nodes
• Immutable append-only log
• Fine-grained access control
• Interoperable with other IPFS tools

Cons

• Still in early development
• Limited query capabilities
• Performance limitations of IPFS
• No built-in indexing or relationships

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

OrbitDB

• Open Source

BigMemory

• Subscription-Based