Modern applications rely on humongous amounts of diverse data from sensors, processes, interactions, etc., to operate efficiently. But unless this data is appropriately managed, there is no way these applications can make sense of the unstructured Big Data and derive business value for successful operations.
Although traditional business applications could easily conform to standard data structures, the complexity of today’s applications requires organizations to rely on multi-model databases that provide the perfect solution to managing heterogeneous data.
What Do Multi-Model Databases Offer?
In today’s era of cloud computing, applications collect and analyze data from different sources, but the information stored isn’t always in the same format or database. Multiple formats make it extremely hard for applications to maintain and leverage diverse data while increasing overall complexity.
Storing data in multi-model database wards off this problem. As a modern management system, multi-model databases offer an elegant solution to managing diverse and unstructured data. Instead of integrating multiple database models, a multi-model database naturally supports multiple data models in their native form using a single, integrated backend.
Such an integrated backend overcomes the problem of data silos and multiple interfaces that require complex integration workflows, facilitating integrated data and providing a unified interface for data consistency, security, and access.
By using the right mix of data models, multi-model databases simplify the underlying data architecture and eliminate the need to orchestrate various services to maintain data consistency and security for end-user consumption.
Since the parameters for how information in a database should be organized and arranged are already defined, teams can easily meet various application requirements in a single database – without having to deploy multiple database systems.
Why Have They Become a Necessity for Modern Applications?
Unlike traditional database management systems that support only a single database model, multi-model databases store, query, and index data from different models, delivering the many advantages of polyglot persistence.
This flexible approach to database management allows modern applications to store varied data in a single repository, thus improving agility and reducing data redundancy.
Let’s look at some reasons why multi-model databases are a must-have for modern applications:
Accommodate Different Data Models
Multi-model databases are great at consolidating and accommodating a variety of data models that today’s applications rely on. From relational and hierarchical to object and document, these databases help application teams support different use cases while also giving them the flexibility to mix and match models to fit their unique application needs.
Running multiple databases means each system could be a single point of failure for the more extensive system and application. Multi-model databases bring down the number of failure points, improving data reliability while also reducing the time it takes to recover from machine failures. Such recovery reduces the impact on monetary costs and helps maintain customer engagement and experience with the application.
Handle Different Forms of Data
With modern applications having to deal with different forms of data from various sources, they need to have the capability to capture, store, and analyze them with high accuracy. Multi-model databases allow app teams to handle different forms of data that do not fit rigid schemas.
Simplify Data Management
Although fragmented database environments help meet the needs of modern applications, they increase the complexity of development and operations. Multi-model databases eliminate the need to maintain multiple database systems, software licenses, developers, and administrators, by providing a single backend that helps maintain data consistency and fault tolerance.
Ensure Seamless Scaling
As modern applications scale horizontally and vertically, database performance must also scale accordingly. Multi-model systems dissociate the query language and data model from the underlying database, allowing app teams to independently scale different components within the architecture as needs change.
Maintain Data Consistency
A unified system that stores data from disparate sources and formats ensures consistency between different models. High-level transaction functionality built into the application ensures transactions across different database systems are supported by a single backend system for distinct application requirements.
Improve Fault Tolerance
Modern applications must be extremely fault-tolerant and respond to failure quickly and efficiently. Multi-model databases equip applications with this ability through the seamless and continuous integration of multiple systems in a single backend. Such integration delivers fault tolerance across the system as a whole.
The Bottom Line
As applications grow in complexity, their database requirements are also mounting. But integrating multiple databases and maintaining consistency between data collected from different sources is a time- and cost-intensive endeavor.
Thankfully, multi-model databases offer a great alternative to building the data models you need on a single backend.
By combining disparate data elements from distinct sources, they pave the way for much-needed scalability, fault tolerance, and high-performance, allowing modern applications to adapt to changing business scenarios and meet evolving customer needs.
The article is written by Anurag Sinha, Co-Founder & Managing Director, Wissen Technology (Wissen.com).