Document databases are riding a wave of popularity among dev teams due to their inherent advantages for modern application development. Statistics paint a clear picture, with research showing that non-relational databases reach 94% satisfaction rates among users. Document databases fall under this type. The trend is expected to continue as developers seek solutions that can handle the complexities of unstructured and semi-structured data, a hallmark of today’s web applications and mobile experiences.
Here are six key reasons why document databases are gaining favor with dev teams:
- Schema Flexibility
Unlike relational databases with pre-defined schemas, a document database offers a schema-less or schema-on-write approach. This means data can be stored in JSON (JavaScript Object Notation) documents, a flexible format that allows for dynamic structures. This freedom empowers dev teams to evolve their data models as their applications and needs change, without costly schema migrations.
Intuit, a leading provider of financial software, uses MongoDB to manage user data and tax information. This flexibility allows them to easily accommodate new features and integrations without altering the core structure of their data model.
- Simplified Development
Document databases often come with intuitive query languages that closely resemble human language. This eliminates the need for complex SQL statements, making it easier for developers to write and maintain queries. Additionally, the elimination of schema constraints allows for faster development cycles, as developers don’t have to spend time wrestling with rigid data structures.
One company reaping the benefits of simplified development is Airbnb. They leverage document databases to manage their content for user engagement and property listings. The flexibility and ease of querying allow them to efficiently retrieve data based on diverse search criteria, ensuring a smooth user experience for both hosts and guests.
- Rich Data Modeling
Documents within a document database can store a variety of data types, including text, numbers, images, and even nested JSON objects. This rich data modeling capability allows developers to represent complex entities and relationships within a single document, reducing the need for complex joins in traditional relational databases.
For example, Forbes uses document databases to store and manage their vast collection of articles, multimedia content, and user data. Data modeling allows them to store not just the article text but also additional details like author information, multimedia assets, and reader comments within the same document, simplifying content management and personalization.
- Horizontal Scalability
Document databases are horizontally scalable, meaning the system can have more servers in the database cluster. Doing so allows for better distribution of load and increases storage and processing capacity at the same time. This lets dev teams build applications that can seamlessly handle massive amounts of data without performance degradation.
A prime example of horizontal scalability in action is Verizon. The company uses document databases to manage its customer base, billing information, and network usage data. This setup ensures that Verizon’s platform can handle the massive volume of data generated by millions of customers.
- Cloud-Native Compatibility
Document databases are often offered as cloud-native solutions. This means they are designed to run on cloud platforms like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). This cloud-native compatibility simplifies deployment, management, and maintenance for dev teams. Additionally, cloud-based document databases offer automatic scaling and pay-as-you-go models, helping businesses optimize their infrastructure costs.
For instance, Discovery Channel uses MongoDB Atlas, the cloud-based version of MongoDB, to manage video content library and user data. This cloud-native approach allows the entertainment provider to scale its database infrastructure efficiently as their viewership and content library grow.
- Enhanced Performance for Modern Applications
Document databases are often optimized for high performance when dealing with large datasets and frequent queries. This makes them ideal for modern applications that require real-time data access and analytics. Additionally, document databases excel at handling unstructured and semi-structured data, which is prevalent in today’s web applications and mobile experiences.
They can be supported by a powerful data management tool, which can act as a bridge between the flexible structure of document databases and the need for data governance and organization. This combined approach empowers developers to leverage the flexibility of document databases for agile development while maintaining data integrity and security – a critical consideration for modern applications.
For dev teams building agile and scalable applications, document databases offer a compelling alternative. The combination of schema flexibility, simplified development, rich data modeling, horizontal scalability, cloud-native compatibility, and enhanced performance makes document databases a powerful tool for the modern development landscape.
