Developments in cloud technology make it possible to replicate almost any data center activity on hosted infrastructure. So, what is so special about cloud databases? And why should you consider moving to a Database as a Service model?
Database-as-a-service (DBaaS) is a cloud computing service. As a hosted/managed service, users don’t have to worry about setting up hardware or installing software. Everything related to managing the database is handled by the service provider.
Database hosting options are available for all database types, including NoSQL, MySQL, and PostgreSQL. MongoDB Atlas is one example of a NoSQL DBaaS service that is easily scalable.
The DBaaS subscription includes everything required to operate a database in the cloud – including database provisioning, licenses, support, and maintenance. Developers can make use of cloud hosted APIs to build out new applications, accessing and manipulating data programmatically. Because of this, DBaaS shares many similarities with other SaaS subscription-based cloud offerings.
As a managed service, there is no additional overhead; you can get right to work extracting value from your data store.
Once the data has been uploaded, the DBaaS database engine itself operates in almost exactly the same way as an on-premises installation. In fact, the very same core is installed in the hosted data center. For developers, DBAs, and data engineers, the experience is almost indistinguishable from working with a local database.
The major difference is the physical infrastructure on which a cloud database runs. In a public Infrastructure as a Service (IaaS) cloud environment like Microsoft Azure, Amazon Web Services (AWS), Google Cloud Platform (GCP), and MongoDB Atlas, the database engine (and data) is run on a shared hardware platform. This adds the compute power, resource elasticity, and scalability needed to support your growing data stores and processing needs.
Cloud database management is often much simpler than traditional on-premises equivalents. The database administration tools themselves are almost identical, allowing you to provision databases quickly and easily on the hosted infrastructure.
The major difference between DBaaS and local deployments is the amount of back-end administration required. Cloud computing principles allow you to offload time-consuming infrastructure administration to the service provider; they are responsible for ensuring the physical and application layers are operational and optimized.
Whether you are an individual developer or operate a team of data engineers and developers, outsourcing infrastructure administration frees you to focus on the data itself, reclaiming time and resources that would normally have been spent on low-level maintenance tasks.
Why should you consider using or moving to a DBaaS? Here are three benefits to consider:
Database sizes continue to grow exponentially, as modern applications now index, search, and process a wide range of file types including video, audio, and other unstructured formats. This requires regular investment in additional storage and processing capacity to accommodate expansion.
With DBaaS, the cloud computing model offers virtually unlimited growth potential without any upfront investment. Your database can continue to grow without concerns about reaching capacity or having to make upfront investments in additional hardware.
DBaaS services are fully managed too, so providers (like MongoDB) take care of infrastructure, hardware, operating system, and software. This frees your time and your developers/data analysts to focus on building your apps, or on extracting value from your database, with no additional resources required to manage and maintain the platform.
Using the Database as a Service model, extending and improving data operations is greatly simplified. The issue of available resources has been resolved (see above), allowing you or your developers to focus on the data – and how to extract new, meaningful insights from it.
Developers can also quickly provision databases as required, easily cloning datasets and configurations without needing assistance from the IT infrastructure team. The provision of APIs as part of the cloud service allows them to build the next-generation applications that businesses need to reach their strategic goals.
The faster developers can perform these relatively simple administration tasks, the sooner they can deliver code updates and improvements that streamline data-driven operations.
Choosing a NoSQL database DBaaS like MongoDB Atlas expands the potential of your big data operations. Unstructured managed databases can be used to deliver data as a service by building an operational data layer (ODL) on top of a NoSQL database.
The ODL makes all your corporate data available on demand, ready for building transformational new applications that help your business do more with the data it owns. An ODL is an important step towards building intelligent, fast, real-time applications.
DBaaS is a logical extension of cloud technologies, using pooled storage and processing capacity to support the changing demands of platform users. With virtually infinite scope for data growth, cloud computing helps to overcome the physical limitations of the local data center.
DBaaS usage is more widespread than you may realize. Small WordPress websites using shared hosting already use a SQL database maintained and operated by the ISP for back-end operations. The site owner pays for web hosting, but an element of DBaaS is included in that fee.
At the other end of the scale, enterprise-class organizations are using SQL and NoSQL databases to build enormous data lakes to power their real-time big data analytics operations. Providers like Microsoft Azure and Google Cloud Platform manage infrastructure and platform, allowing clients to focus on building complex, real-time applications that power their operations.
DBaaS is a good fit for any application that needs scalability and flexibility for their databases.
Choice of DBaaS will depend on your operational needs. In many cases, you could potentially choose a like-for-like replacement, migrating your existing relational database to a cloud-hosted equivalent.
Alternatively, you could opt for an unstructured NoSQL database, offering maximum flexibility should your data needs change in the future. MongoDB is a non-relational database that allows you to save raw, unedited data, ensuring every detail remains available if your operational needs change.
All database types have their merits, but selecting the right database should be led by use case and the expertise within your engineering team. Unstructured databases offer greater flexibility and scalability but at the cost of losing transactional guarantees provided by a structured alternative.
Like any other “as a service” offering, DBaaS is a platform for hosting your data using your database engine of choice. With a hosted database service, everything you need — infrastructure, storage, database software, licenses (where required), replication, fail-over, and backup automation — are included as part of the subscription fee.
Cloud computing makes it possible to build truly scalable databases. Pooled resources allow your database to grow, or to access additional processing power, as and when required. This is particularly useful for non-relational databases like MongoDB that are designed to scale horizontally for convenience and cost control reasons.
MongoDB Atlas is a non-relational database hosted on your cloud platform of choice. The database can be deployed on Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP) to match your corporate cloud specifications and strategy.
Platform as a Service provides a platform for their customers to run their business application on without the need to build and maintain infrastructure that is typically required by a software development process.
DBaaS is not a PaaS. The cloud database sits on top of the platform at the application layer. When using a DBaaS service, the costs of the underlying platform are included in the subscription.
Data as a Service (DaaS) is concerned with turning raw data data into meaningful and actionable intelligence. Although it uses technology to achieve these goals, Data as a Service is not a technology service. Because DBaaS is concerned with database engines storing raw data and the underlying infrastructure, it is distinctly different from DaaS.
Yes, MongoDB can be installed and run from the Amazon Web Services (AWS) platform, either as a managed service with MongoDB Atlas or self-managed.
Yes, the MongoDB database service can be installed and run from the Microsoft Azure platform. It’s available as a managed Database as a Service with MongoDB Atlas, or can be self-managed on Azure.
Yes, the MongoDB database service can be installed and run from the Google Cloud Services (GCS) platform. You can run MongoDB on GCP either with MongoDB Atlas, or you can self-manage.
MongoDB database management systems can be installed and run in a private cloud environment on-premises. You will not receive the same benefits of the managed service in this model. However, you will need to create and maintain your own high-availability and fail-over infrastructure, for instance.