Database cloud services refer to options for storing data; whether it is a managed relational SQL database that’s globally distributed or a multi-model NoSQL database designed for any scale. In the last few years, Amazon Web Services and Azure are trying to provide services that can provide conclusive analytics from complex databases. Although Amazon Web Services vs Azure has always been a tough battle to conclude on, we can still explore them on the grounds of database services.
Why cloud providers are offering top-notch database services?
The public cloud is changing the ways how enterprises host, manage and scale their database operations. It gives freedom to scale at any rate and provisions for critical needs. This, therefore, eliminates hardware procurement and installing processes. Organizations can take advantage of cloud-native technologies each time they store and analyze their data. In addition, Gartner recommends that enterprises should make cloud databases their preferred deployment model for all new business processes, workloads, and applications.
In other words, enterprises which prefer a hybrid cloud model can leverage database services. This can be done by deploying and analyzing database in the cloud environment. Then transferring analyzed data in on-premise data centers.
Amazon Web Services vs Azure vs Google Cloud Platform
Now, it’s easier than ever to migrate and maintain their databases. Given that Amazon Web Services and Azure, both offer a variety of managed database services; it can be hard to comprehend. So, let’s compare them.
|1||Relational Database Management Service
(SQL Database is a high-performance, reliable, and secure database you can use to build data-driven applications and websites, without needing to manage infrastructure.)
|Azure SQL Database
SQL Server Stretch Database
Azure Database for MySQL
Azure Database for PostgreSQL
|2||Non-relational Database Management Service
(A globally-distributed, multi-model database that natively supports multiple data models: key-value, documents, graphs, and columnar.)
DynamoDB Accelerator (DAX)
Azure Time Series Insights
Firebase Realtime database
|3||Time series Database
(A non-relational data store for semi-structured data.)
|Amazon DynamoDB||Azure Time Series Insights||Cloud Bigtable|
|4||In-Memory Data Store
(An in-memory–based, distributed-caching service that provides a high-performance store typically used to offload non-transactional work from a database.)
|Amazon ElastiCache||Azure Redis Cache||Cloud Memorystore|
(A fully managed data warehouse that analyzes data using business intelligence tools.)
|Amazon Redshift||Azure SQL Data Warehouse||BigQuery|
The most important key tip to put into work is testing all the service by yourself. Consider every service in terms of:
- ease of use and
- potential to scale which will help you project the performance & cost.
If you have a scalable database, then you can have trial deployments. This will reveal key insights to choose the required database services.
In conclusion with Amazon Web Services vs Azure; to select the best suitable option while researching database services, consider the technical aspects of each service. For example, consider how to implement security and compliance. After that, research what programming language a particular database service uses. This is because you need to know, will it suffice your application architecture or not.
Also, the ecosystem of AWS with third-party vendors and Azure’s hybrid capabilities may prove vital to making the decisions for database services.
If you are looking for a cloud service provider that can fulfill all your needs, then you should consider an extensive comparison to gain a clear picture of what the leading cloud players have to offer. Download the most elaborative comparison sheet between AWS and Azure.