What are Cloud-Native Databases?

Cloud-native databases are built specifically for cloud environments, utilizing the scalability, elasticity, and distributed architecture of cloud infrastructure.

They’re constructed from the ground up to flourish in the cloud, unlike conventional databases, which were designed for on-premises surroundings and often struggle to adapt to the cloud’s active nature.

• High scalability, availability, and cost efficiency are key considerations for customer satisfaction.
• Some famous products in this category are Amazon DynamoDB, Google Cloud Spanner, and MongoDB Atlas.
• Cloud-native databases should be used where your applications require high scalability, you deal with enormous amounts of data, or you want to minimize operational costs.

The main difference is based on scale, architecture, and the approaches used to achieve availability. Cloud-native databases are designed to add nodes horizontally to achieve high availability and performance in the cloud. Traditional databases, on the other hand, are typically planned for vertical scaling and may fight to adjust to the cloud’s active nature.

Cloud-native data storage can integrate attributes such as a distributed architecture, managed services, and pay-as-you-go pricing, which may contribute to their compatibility with certain modern, cloud-based applications.

Easy scalability, high availability, low costs, and minimal functional overhead are some of the perceived benefits of products in this category. Cloud-native databases can rapidly outscale or downscale in response to load conditions, which means there is rarely a need for databases to be offline. 

Pay-as-you-go services offer flexible payment based on usage, while fully managed services may help reduce the need for manual configuration and maintenance.

Emerging issues operating key issues are interrelated, and they include vendor lock-in, data migration, and skills to deploy and manage these databases.

It is crucial to consider how effortless it is to move the data in case possible difficulties appear in data migration and to have a clear idea of the database management experience or the possibility of addressing managed services.

Notable examples include:

• Amazon DynamoDB: A NoSQL database is often used for high-performance applications that require flexibility in data modeling.
• Google Cloud Spanner: It leverages a distributed architecture across various locations in its relational database, aiming to concurrently achieve data consistency and service availability.
• MongoDB Atlas: A document-oriented database designed for flexibility and scalability, typically used in cloud-based environments.
•  Azure Cosmos DB: This is a type of database that is hosted in the cloud and can work with different data models and protocols.

Industry utilization cases involve e-commerce platforms, gaming applications, and IoT devices.

Use cloud-native databases when your applications need to be highly scalable and available when you will process a large amount of data, when you want to spend minimal time on operations, or when creating new applications cloud-native.

Cloud-native databases are designed for the cloud environment. While they may offer advantages over traditional or SaaS solutions regarding scalability, flexibility, and cost-efficiency, these benefits may not be fully realized in the long run.

If your needs are relatively basic, and your demands can be easily predicted, then a SaaS solution would be the best place to start. Nevertheless, when your application gets more complicated and your company needs more independence and customization, a cloud-native database may be the best solution.