ArangoDB
ArangoDB is a graph database that combines graphs, documents, and key-values in a single engine to simplify your data architecture and accelerate complex application development.
TigerGraph
TigerGraph is a native parallel graph database platform designed to help you analyze massive datasets in real-time to uncover complex relationships and hidden patterns across your business data.
Quick Comparison
| Feature | ArangoDB | TigerGraph |
|---|---|---|
| Website | arangodb.com | tigergraph.com |
| Pricing Model | Freemium | Freemium |
| Starting Price | Free | Free |
| FREE Trial | ✓ 14 days free trial | ✓ 0 days free trial |
| Free Plan | ✓ Has free plan | ✓ Has free plan |
| Product Demo | ✓ Request demo here | ✓ Request demo here |
| Deployment | ||
| Integrations | ||
| Target Users | ||
| Target Industries | ||
| Customer Count | 0 | 0 |
| Founded Year | 2012 | 2012 |
| Headquarters | San Francisco, USA | Redwood City, USA |
Overview
ArangoDB
ArangoDB is a flexible graph database that lets you store and query data as documents, graphs, or key-values within a single engine. You can build complex applications without the headache of managing multiple database technologies or worrying about data consistency across different systems. By using one query language, AQL, you can perform joins, graph traversals, and geo-spatial lookups in a single request.
You can scale your deployments from a single instance to massive clusters using the ArangoGraph Insights Platform, their fully managed cloud service. It is particularly effective if you are dealing with highly connected data, such as fraud detection systems, knowledge graphs, or recommendation engines. The platform helps you reduce architectural complexity while maintaining high performance for deep-link analytical queries.
TigerGraph
TigerGraph is a high-performance graph database that lets you explore and analyze interconnected data at massive scale. Unlike traditional databases that struggle with complex relationships, you can use TigerGraph to link billions of entities and run deep-link queries in seconds. It combines the power of a native graph engine with the scalability of a distributed system, making it ideal for fraud detection, supply chain optimization, and customer 360 initiatives.
You can build your data models visually and write queries using GSQL, a powerful language that feels familiar if you already know SQL. The platform handles both transactional and analytical workloads simultaneously, so you don't have to move data between different systems. Whether you are a data scientist looking for better features for machine learning or a developer building real-time recommendation engines, you get the speed and scale needed for enterprise-grade applications.
Overview
ArangoDB Features
- Multi-Model Engine Combine graph, document, and key-value data models in one place to simplify your backend infrastructure.
- ArangoDB Query Language Use a single, human-readable language to perform complex graph traversals and document joins in one query.
- SmartGraphs Scale your graph data across multiple nodes while maintaining high performance for complex, deep-link traversals.
- Integrated Search Retrieve information quickly with a built-in full-text search engine that works natively with your stored data.
- ArangoGraph Cloud Deploy and manage your databases in a fully automated cloud environment across major providers like AWS and Azure.
- Microservices Framework Build and run data-intensive microservices directly inside the database using the integrated Foxx JavaScript framework.
TigerGraph Features
- Native Parallel Graph. Execute complex queries across billions of vertices and edges simultaneously to get real-time results from your largest datasets.
- GSQL Query Language. Write powerful, high-level queries with a language that combines the familiarity of SQL with the flexibility of graph traversals.
- Distributed Architecture. Scale your database horizontally across multiple nodes to handle massive data growth without sacrificing performance or speed.
- GraphStudio UI. Design your graph schema, map data, and explore results visually through an intuitive web-based interface for faster development.
- Deep Link Analytics. Traverse 10 or more hops across your data to uncover hidden relationships that traditional databases simply cannot find.
- Multi-Graph Security. Create multiple logical graphs on a single cluster to securely share data across different teams and departments.
Pricing Comparison
ArangoDB Pricing
- Open-source core engine
- Multi-model support
- AQL query language
- Self-managed deployment
- Community-based support
- Everything in Community, plus:
- 14-day free access
- Fully managed deployment
- One-click cluster setup
- Integrated search and graph
- Automated backups
TigerGraph Pricing
- 1 graph solution
- Up to 50GB storage
- Shared CPU resources
- Community support
- Access to 20+ starter kits
- Everything in Free, plus:
- Dedicated instances
- Scalable storage options
- Backup and restore
- Standard support
- Pay-as-you-go pricing
Pros & Cons
ArangoDB
Pros
- Unified query language simplifies complex data operations
- Excellent performance for deep graph traversals
- Flexible schema allows for rapid prototyping
- Active community and helpful documentation
- Eliminates the need for multiple database types
Cons
- Learning curve for mastering AQL syntax
- Memory consumption can be high for large datasets
- Cloud pricing can become complex to predict
TigerGraph
Pros
- Exceptional performance on deep-link queries
- Scales horizontally to handle massive datasets
- GSQL language is powerful and expressive
- Visual design tools simplify graph modeling
- Excellent for real-time fraud detection use cases
Cons
- Steep learning curve for GSQL language
- Documentation can be difficult to navigate
- Requires significant memory for large graphs