Exploring Serverless Databases
2 Minutes Serverless Reads — #03
In modern-day computing, databases play a vital role, allowing us to organize, store and retrieve data efficiently. Databases are the backbone of an application, be it websites or enterprise systems. It’s fair to say that the way data is stored in databases is crucial in fetching the required data. As serverless computing continues to gain traction, Amazon Web Services(AWS) has also produced some of the best serverless databases in the market.
1. Amazon Aurora Serverless
Aurora Serverless is a relational database service that provides the benefits of Relational databases along with the scalability of a serverless architecture allowing the devs to harness the power of serverless at scale. It’s compatible with MySQL and PostgreSQL. Aurora claims to be 5x faster than MySQL and 3x faster than Postgres.
Key Features:
Autoscaling: Aurora automatically adjusts its capacity based on incoming requests. It’s remarkably scalable that can instantly scale to thousands of transactions within a fraction of a second, which helps in optimizing the costs and maintaining performance.
High availability: It replicates data across multiple AZs for durability and fault tolerance providing upto 15 read replicas for smooth reads. Amazing!
Seamless maintenance: With serverless databases, patching, backups, and software updates are handled by the cloud provider without affecting the application. Hence provisioning and maintenance are not developer issues.
Check out more features here.
2. Amazon DynamoDB
Amazon DynamoDB is a fully managed NoSQL database service, which means unlike any other relational databases where the data is stored in columns and rows, in a NoSQL database, the data is stored in the form of documents, imagine a JSON Object, where each record consists of key-value pairs. It’s amazingly suitable for applications with rapidly changing workloads, such as gaming, e-commerce, and IoT.
To know DynamoDB in a wider picture, check this out — All you need to know about the Amazon DynamoDB.
Key Features
Autoscaling: DynamoDB automatically adjusts read and write capacity based on the traffic-patterns of your application.
Fully managed: AWS takes care of operational tasks such as provisioning the hardware, patching software, and database backups.
Encryption at Rest: By default, DynamoDB encrypts the data at rest to ensure security of the data.
Multi-region replication: Provides high availability and disaster recovery through global tables that replicate data across multiple AWS regions.
Check out more features here.
3. Amazon Neptune
Amazon Neptune is a fully managed graph database service that allows developers to build interactive graph applications that can query billions of relationships in milliseconds. It’s optimized for storing and querying data with complex relationships, making it ideal for applications that need to analyze highly connected data sets.
Key Features:
High Availability and Secure: Amazon Neptune is highly available that is the data is stored across AZs, also by providing 15 read replicas that will be available as a failover.
Graph database engine: Neptune is designed to efficiently handle graph data, making it easy to model and query relationships between data points.
High performance: It provides high throughput and low-latency queries, even on large graph datasets. Neptune efficiently stores and navigates graph data.
ACID compliance: Neptune ensures data integrity with support for ACID transactions.
Check out more features here.
4. Amazon DocumentDB
Amazon DocumentDB is a fully managed document database service designed to work with MongoDB applications. It offers the flexibility of a document model while providing the performance, scalability, and reliability required for production workloads. The migration is super seamless when it comes to MongoDB-based applications with very less or no change at all.
Key Features:
Compatibility: DocumentDB supports MongoDB API, making it easy to migrate existing MongoDB applications.
Scalability: It provides high-throughput read and write operations, with autoscaling to handle varying workloads.
Data durability: Offers continuous backups, automated failover, and point-in-time recovery to ensure data integrity.
High performance and throughput: DocumentDB provides 15 read replicas to support high-volume application requests.
Check out more features here.
Conclusion
These serverless databases provide different ways to handle various data storing and accessing capabilities based on application needs, allowing the developers to solely focus on what matters. Code!
