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.

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.

OrbitDB

OrbitDB

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.

Categories:
Development Databases
decentralized peertopeer ipfs distributed-web

OrbitDB Features

  1. Decentralized database
  2. Built on IPFS
  3. Event log for database changes
  4. Supports CRUD operations
  5. Access control lists
  6. Queryable database API

Pricing

  • Open Source

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

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