Over the last few years it has been fascinating to see how organizations evolve their data management and application development environments. Traditionally, companies depended on monolithic architectures that initially served them well, however today’s on-demand business environment calls for a model that can support a more flexible, microservices-driven approach, and facilitate the pace of innovation. Why is this trend towards microservices and a DevOps approach becoming so pervasive? The answer relates to a higher-level trend: the push towards on-demand IT, as the focus has shifted to prioritize the developer experience, and the specific technologies they are using.
Microservices are an architectural model that give developers a way to design highly scalable and flexible applications by decoupling the application into distinct services that perform specific functions. Modern applications are not uniform—they vary greatly in the data volume and data types they utilize. In addition, applications often have unique requirements in the form of latency or scale. Therefore, application developers no longer want to be tied to a single, over-burdened, database. This differs greatly from systems built on monolithic structures where services are tightly coupled and must be scaled together, creating operational challenges. Amazon Web Services (AWS) created a portfolio of purpose-built databases to assist with this movement.
AWS offers a broad and robust collection of purpose-built databases that support diverse data models, and allow customers to build data-led, highly scalable, distributed applications. This enables customers to pick the best database to solve a specific problem, and break away from restrictive commercial databases, to focus on building applications.
Optic One: AWS database portfolio and use cases
For example, in 2019, AWS launched Amazon DocumentDB (with MongoDB compatibility) as customers showed increasing demand for a fully managed cloud database to support document-oriented data. Working backward from the capabilities customers requested, DocumentDB was purpose-built for scalability, fully managed and integrated with AWS, and enterprise-ready with high durability. Document databases had become very popular in recent years, in part due to the explosion of content being created across varying media types. A document database is a type of nonrelational database that is designed to store massive volumes and query data as JSON-like documents. Document databases make it easier for developers to store and query data in a database by using the same document-model format they use in their application code. The flexible, semi-structured, and hierarchical nature of documents and document databases allows them to evolve with applications’ needs. The document model works well with use cases such as catalogs, event logs, user profiles, mobile applications, personalization, application modernization, and content management where each document is unique and evolves over time. Document databases enable flexible indexing, powerful ad hoc queries, and analytics over collections of documents.
“FINRA’s Data Collection platform stores millions of regulatory filings from hundreds of thousands customers, such as broker dealers, investment advisors, and stock exchanges. Our old platform was built using a relational database that stored data in XML, which had a rigid query structure and required us to write custom code for data versioning and schema validation. We chose Amazon DocumentDB because it natively stores data in JSON, making it simpler to query and index regulatory documents. This reduces our development cycles, while extending the usability of our data by easily integrating with other systems that leverage JSON. Because DocumentDB is a fully managed service, our databases are scalable, highly available, backed up, and encrypted without any overhead from our engineering teams.”
Ranga Rajagopal, Senior Director, Enterprise Data Platforms – FINRA
Two of the primary challenges customers face with document databases include the multitude of undifferentiated administrative tasks, and the struggle to scale their database (the latter being so complex that it creates additional challenges in the form of increased cost, loss of team productivity, and technical pitfalls). With Amazon DocumentDB, you don’t need to worry about database management tasks, such as hardware provisioning, patching, setup, and configuration. Built ground-up for the cloud, Amazon DocumentDB is engineered with scalable workloads in mind. DocumentDB decouples compute and storage, allowing each to scale independently. By breaking apart the monolith, customers will experience simplified orchestration, faster deployment of resources, no single point of failure, better performance, and no strangulation point. As an example, with Amazon DocumentDB you can perform backups even during peak traffic periods, ensuring you always maintain data resiliency and integrity, while supporting the compute demands of your critical applications.
Two of the primary challenges customers face with document databases include the multitude of undifferentiated administrative tasks, and the struggle to scale their database (the latter being so complex that it creates additional challenges in the form of increased cost, loss of team productivity, and technical pitfalls). With Amazon DocumentDB, you don’t need to worry about database management tasks, such as hardware provisioning, patching, setup, and configuration. Built ground-up for the cloud, Amazon DocumentDB is engineered with scalable workloads in mind. DocumentDB decouples compute and storage, allowing each to scale independently. By breaking apart the monolith, customers will experience simplified orchestration, faster deployment of resources, no single point of failure, better performance, and no strangulation point. As an example, with Amazon DocumentDB you can perform backups even during peak traffic periods, ensuring you always maintain data resiliency and integrity, while supporting the compute demands of your critical applications.
“On one of our clouds, users are making like 50,000 API calls a minute, and Amazon DocumentDB is not really blinking an eye.”
Robert Miller Software Development Lead for Public APIs, Plume
To further support customers, Amazon DocumentDB recently announced a new feature called Global Clusters. Global Clusters provides disaster recovery from region-wide outages and enables low-latency global reads. Global Clusters helps you support critical, global workloads by automatically replicating data across multiple AWS regions, with sub-second latencies. The primary benefits of Global Clusters are—
- Disaster recovery from region-wide outages
- Global reads with low latency
- Scalable secondary clusters
- High-speed replication across clusters
To summarize, Amazon DocumentDB helps customers to scale and innovate faster thanks to three key functionality pillars. First, since DocumentDB is a fully managed service, customers can see a meaningful reduction in administrative activities, thus freeing up developers and application owners to spend more time iterating and innovating on their applications. Second, DocumentDB’s unique architecture allows for easier and faster scaling of resources, thereby reducing time to value and ensuring your applications keep pace with end user demand. Third, DocumentDB easily integrates with other AWS cloud services. Most Amazon DocumentDB customers also use other AWS nonrelational or relational database services for a unified data management experience, where teams can leverage their existing AWS skills and expertise. In particular, DocumentDB is commonly used in conjunction with Amazon ElastiCache to accelerate key applications. Finally, DocumentDB easily connects to AWS analytics services such as Redshift, Athena, Kinesis, or 3rd party, qualified, applications from AWS Marketplace.
“At Knotion, we use Amazon DocumentDB (with MongoDB compatibility) for our learning module called Class Journey. With Class Journey, thousands of students can track their progress across several tasks in the module. All activity for our learning module is modeled as JSON documents in Amazon DocumentDB. We chose Amazon DocumentDB because of its unique architecture, reliability, scalability, performance, and seamless integration with other AWS services such as Lambda, S3, and Elastic Beanstalk. Particularly painful database management tasks such as backups, patching, setting up high availability, and scaling are available out of the box, freeing up our time to improve Knotion’s learning modules rather than managing our databases.”
Hernan Ramirez Mirabent, CTO – Knotion
To find out how customers across verticals and geographies are using DocumentDB, visit our customer reference page to see how the BBC, Dow Jones, Capital One, Samsung, the Deutsche Fußball Liga (DFL), and many other customers have found value in the implementation of Amazon DocumentDB. To learn more about DocumentDB and AWS purpose-built databases visit our portfolio home page. And to gain additional details on DocumentDB’s newest feature, Global Clusters, view our complimentary on-demand webinar.