FleetDB vs Titan Database

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

FleetDB is a Business & Commerce solution with tags like time-series, metrics, sensor-data, events, lightweight, scalable, docker, kubernetes.

It boasts features such as Time series data storage, High write throughput, Fast reads, Numeric data optimization, Lightweight, Scalable, Docker and Kubernetes deployments and pros including Open source, Fast performance, Scalable, Lightweight, Easy deployment.

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.

Feature	FleetDB	Titan Database
Overall Score	N/A	N/A
Primary Category	Business & Commerce	Development

Product Overview

FleetDB

Description: FleetDB is an open-source time series database optimized for fast reads and writes of numeric data. It is useful for capturing metrics, sensor data, and events. FleetDB is lightweight, scalable, and easy to deploy in Docker and Kubernetes.

Titan Database

Description: 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.

Key Features Comparison

FleetDB Features

• Time series data storage
• High write throughput
• Fast reads
• Numeric data optimization
• Lightweight
• Scalable
• Docker and Kubernetes deployments

Titan Database Features

• 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

Pros & Cons Analysis

FleetDB

Pros

• Open source
• Fast performance
• Scalable
• Lightweight
• Easy deployment

Cons

• Limited documentation
• Not ideal for non-numeric data
• No built-in monitoring or alerting
• Limited ecosystem compared to more established databases

Titan Database

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

Pricing Comparison

FleetDB

• Open Source

Titan Database

• Open Source
• Custom Pricing