The Guide for Time Series Data Projects is out.

Download now
Skip to content

What is a Multi-Model Database?

Have you wondered how much data is generated every day? The past decades have seen an explosion of data, and this brings many benefits for businesses. However, they also face the challenge of managing it. One solution is changing the data management game: multi-model databases.

The Solution for Modern SaaS Applications

Modern SaaS applications have diverse database workloads, providing a real-time view of data over time, interactive analytics to explore recent and historical data, full-text search on product information, and APIs. Each of these functionalities has different data write needs and access patterns and may use other data models. The common practice in recent years has been to use specialized database technology for each of these data models and workload types for a SaaS application.  

This is where multi-model databases come in, as they offer a more straightforward solution for modern SaaS.  

In a nutshell, a modern application needs multiple data models, and different data types may demand additional data models depending on their use and access patterns. A multi-model database is a type of database that supports storing, processing, and accessing multiple types of data models like document files, key-value, vectors, and relational models, all within a single, integrated backend. 

Having data stored in a multi-model database enables the user to query it across the data more effectively. This eliminates the need to implement different storage solutions for data analysis.

The Benefits of a Multi-Model Database

Implementing the database of an enterprise application using a multi-model database opens opportunities for leveraging the full potential of your data as the access becomes simplified, offering several benefits:

  • Easier application development: Using a multi-model database can help reduce infrastructure costs and increase your team's availability. This is because they won't have to spend extra time learning various query dialects, SDKs, and consoles that are associated with each component of a polyglot persistence setup.
  • Data consolidation: Businesses gather data from several sources. Multi-model databases can integrate different data sources since they can natively support many different models. Plus, they streamline the process of viewing and analyzing data from different sources simultaneously, reducing the workload.
  • Cost efficiency: Maintaining multiple databases can be costly. However, by merging them into a single multi-model database, businesses can save on both operational and infrastructure costs. Multi-model databases simplify your application architecture by giving you a single point of contact for the development and consumption of several data systems with different data models.  
  • Simplified architecture: Managing and integrating multiple standalone databases is no longer necessary with multi-model databases, simplifying the architecture.
  • Improved Performance: Optimized for handling diverse data models, they can offer better performance for complex queries that span multiple data types.
  • Scalability: Many multi-model databases are designed to be highly scalable, handling large volumes of data efficiently. 

CrateDB: A Multi-Model Database  

CrateDB is a multi-model database that efficiently handles multiple data models within the same database, including structured data (tables, time series, geospatial), semi-structured data (JSON/documents), and unstructured data (text, vector, binaries like documents, images, and videos). It eliminates the need to manage and synchronize multiple database technologies and learn different languages by offering unified access via the well-known SQL language.  

It is a powerful data storage solution that provides flexible schema options, allowing for the storage of complex and nested objects. CrateDB supports the insertion of data as a JSON string, and new columns can be added dynamically to adapt to changing needs. Additionally, all data models are accessible via SQL, which enables complex queries and full-text search. CrateDB's schema flexibility eliminates the traditional pain of rigid relational schemas, making it a versatile option for data storage.  

If you're looking for a multi-model database that can adapt to your changing data needs, CrateDB is worth considering.