MongoDB vs Titan Database

Struggling to choose between MongoDB and Titan Database? Both products offer unique advantages, making it a tough decision.

MongoDB is a Development solution with tags like nosql, document-database, open-source.

It boasts features such as Document-oriented storage, Automatic sharding, Rich and expressive query language, High availability, Horizontal scalability and pros including Flexible schema, High performance, Easy scalability, Rich query capabilities, High availability.

On the other hand, Titan Database is a Development product tagged with graph, database, distributed, scalable.

Its standout features include Distributed graph database, Highly scalable, Real-time data access, ACID transactions, Multi-model storage, Elastic scaling, Global graph analytics, Native integration with Apache Spark & Apache TinkerPop Gremlin, and it shines with pros like High performance, Scalability, Fault tolerance, Flexibility, Open source.

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.

MongoDB

MongoDB

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.

Categories:
nosql document-database open-source

MongoDB Features

  1. Document-oriented storage
  2. Automatic sharding
  3. Rich and expressive query language
  4. High availability
  5. Horizontal scalability

Pricing

  • Open Source
  • Subscription-Based

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


Titan Database

Titan Database

Titan is an open-source, distributed graph database optimized for storing and querying graphs containing hundreds of billions of vertices and edges distributed across a multi-machine cluster. It is highly scalable and provides real-time data access through a transactional database.

Categories:
graph database distributed scalable

Titan Database Features

  1. Distributed graph database
  2. Highly scalable
  3. Real-time data access
  4. ACID transactions
  5. Multi-model storage
  6. Elastic scaling
  7. Global graph analytics
  8. Native integration with Apache Spark & Apache TinkerPop Gremlin

Pricing

  • Open Source
  • Custom Pricing

Pros

High performance

Scalability

Fault tolerance

Flexibility

Open source

Cons

Steep learning curve

Limited ecosystem compared to other databases

Not ideal for non graph workloads