A multi-model database is a type of database that supports multiple data models — such as key-value, document, graph, relational, and columnar — within a single unified backend. This means you can store and query different types of data using the most appropriate model, without needing multiple database systems.
Multi-model databases provide flexibility and efficiency by allowing developers and analysts to work with diverse datasets while maintaining consistency, security, and scalability — all in one place.
Why Multi-Model Databases Matter
Traditional databases typically follow a single data model. But today’s applications often require different models for different tasks — for example:
- User profiles in document format
- Relationships stored as a graph
- Log data handled as time-series or columnar records
- Real-time session data stored as key-value pairs
Instead of integrating and managing multiple systems, a multi-model database handles all these needs, reducing complexity and boosting performance.
Supported Models in Multi-Model Databases
- Document: JSON/BSON documents (e.g., for user data, content)
- Key-Value: Simple, fast storage of session or configuration data
- Graph: Nodes and edges for relationships and networks
- Relational: Traditional tables with SQL queries
- Columnar: High-speed analytics over large datasets
Benefits of Multi-Model Databases
- Consolidation: One platform for multiple data types
- Reduced complexity: Fewer systems to integrate and maintain
- Improved performance: Use the best model for each data access pattern
- Developer agility: Build more flexible applications without rigid schema constraints
- Cost-efficiency: Eliminate the need to license and scale multiple tools
Common Use Cases
- Omnichannel customer platforms: Combine user profiles (document), relationships (graph), and activity logs (time-series)
- IoT platforms: Handle device data in time-series and configuration in key-value pairs
- Financial apps: Use relational tables for transactions and documents for regulatory metadata
- E-commerce platforms: Manage product catalogs, customer relationships, and analytics in one system
Popular Multi-Model Databases
| Database | Description |
|---|---|
| ArangoDB | Supports document, graph, and key-value models with a unified query language (AQL) |
| OrientDB | Combines graph and document models with ACID compliance |
| MarkLogic | Enterprise multi-model database with document, graph, and relational support |
| Couchbase | Combines key-value and document storage with SQL-based querying |
| Azure Cosmos DB | Globally distributed database supporting document, graph, and key-value models |
How ClicData Works with Multi-Model Data
ClicData enables you to connect to a variety of data models — whether through native connectors or APIs — and blend them seamlessly for analysis and visualization.
- Pull data from REST APIs, SQL databases, or NoSQL stores
- Transform document or graph-based data into tabular format for dashboards
- Unify data from multiple sources into a single workspace
- Create live dashboards from multi-model datasets
With ClicData, even complex multi-model data environments can be made report-ready — helping you turn diverse datasets into actionable insights.