Amazon DynamoDB vs Google Cloud Datastore: What are the differences?

Introduction

Amazon DynamoDB and Google Cloud Datastore are both NoSQL databases that offer scalability, flexibility, and high-performance storage solutions. However, there are key differences between the two that make each service unique. In this article, we will explore these differences in detail.

1. Data Model: One of the key differences between Amazon DynamoDB and Google Cloud Datastore is their underlying data model. DynamoDB uses a key-value store model, where each item is uniquely identified by its primary key. Datastore, on the other hand, uses an entity model, similar to a relational database, where data is structured into entities with properties and relationships.

2. Consistency Model: DynamoDB provides eventual consistency by default, meaning that it allows for some delay in the propagation of updates across all replicas. However, it also offers strong consistency as an option. In contrast, Datastore guarantees strong consistency for all reads and writes, ensuring that all replicas are always up to date.

3. Scalability: DynamoDB is designed to scale horizontally, allowing you to add more read and write capacity as your application needs grow. It automatically handles the distribution of data across multiple servers. Datastore, on the other hand, scales vertically, meaning that you can increase the storage capacity and performance of an individual entity as needed.

4. Query Capabilities: DynamoDB provides a flexible query language called DynamoDB Query, which allows you to retrieve data based on conditions and filters. Datastore, on the other hand, offers a powerful query language called GQL (Google Query Language) that supports complex queries with filtering, sorting, and projection.

5. Secondary Indexes: DynamoDB supports global secondary indexes, which allow you to create additional indexes on non-key attributes for efficient querying. Datastore, on the other hand, supports automatic indexing on all properties of an entity, making it easier to query data without the need for explicit indexing.

6. Pricing Structure: The pricing structure of DynamoDB is based on provisioned throughput, storage, and data transfer. You pay for the read and write capacity units that you provision. Datastore, on the other hand, has a pricing structure based on the number of entities, entity reads/writes, and storage usage. You pay for the number of entities you store and the operations you perform on them.

In summary, Amazon DynamoDB and Google Cloud Datastore differ in their data models, consistency models, scalability approaches, query capabilities, secondary index support, and pricing structures. The choice between the two depends on your specific requirements and the nature of your application.