Unlocking Data Potential: The Advantage of Multi-Model Databases

In today's data-driven landscape, businesses face an unprecedented explosion of diverse data types, necessitating a vast array of database options to handle specific workloads. This has resulted in a complex landscape of database management systems, with organizations relying on multiple databases to address the data challenges. 

Operational databases manage daily transactions, time series databases track sensor data, analytical databases support data exploration, graph databases map relationships, data lakes house raw data, master data stores hold core business information, ERP systems manage resources, and caching databases enable fast response times. Moreover, various data types require different structures, leading to a proliferation of database solutions. 

While utilizing multiple databases can address specific needs, it also introduces significant interoperability, administrative, and cost challenges. The question is, can we consolidate data tasks more efficiently and cost-effectively, empowering businesses to manage their data landscape more efficiently? 

Multi-model databases offer a promising solution. These integrated databases can store, manage, and query data in multiple models, simplifying data management and unlocking new possibilities for applications. The landscape of database management systems is witnessing a surge in multi-model solutions, with eight out of the top 10 DBMS listed on db-engines falling under this category. 

Related:Graph Databases: What They Are and How to Get Started

When evaluating multi-model databases, IT leaders should look for attributes like automatic data updates across models, global deployment capabilities, cross-model data processing languages and optimizers, and robust security features to protect sensitive data. By adopting multi-model databases with these characteristics, organizations can simplify data management, handle growing data volumes with ease, enable seamless data analysis across models, and reduce costs through consolidation. 

While multi-model databases offer significant advantages, there may still be cases where specialized databases are necessary, particularly when a dominant data type is involved in the workload. However, by considering multi-model databases for our applications and enterprise architecture, we can foster innovation, improve decision-making, and unlock new possibilities for our organizations. Moreover, many organizations already have multi-model databases but haven't leveraged them beyond a single model, missing out on opportunities. By recognizing the potential of multi-model databases, we can revolutionize our approach to data management and unlock more potential in data. 

Related:Enterprise Data Integration: Now More than Ever