Top 20 AWS DynamoDB interview Question and Answer
Get prepared for your DynamoDB interview with these top 20 frequently asked questions and answers. Covering topics such as key features, scaling, data consistency, use cases, real-time analytics, data storage, data types, durability and availability, integrations with other AWS services, querying data, and secondary indexes. Master these concepts and ace your DynamoDB interview.
What is DynamoDB?
DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability.
What are the key features of DynamoDB?
Some key features of DynamoDB include: fully managed, scalable, and fast performance, support for both document and key-value data models, and support for streams and global tables.
How does DynamoDB handle scaling?
DynamoDB is designed to scale automatically to accommodate the rate of incoming requests and maintain low-latency performance. It uses adaptive capacity to automatically adjust read and write capacity settings based on actual traffic patterns.
How does DynamoDB handle data consistency?
DynamoDB provides four consistency levels for read operations: eventually consistent, strongly consistent, transactional consistent, and parallel scan consistent. You can choose the appropriate consistency level for your use case.
What are some common use cases for DynamoDB?
Some common use cases for DynamoDB include: storing user profiles, storing session data for web applications, storing metadata for serverless applications, and storing real-time analytics data.
Can DynamoDB be used for real-time analytics?
Yes, DynamoDB can be used for real-time analytics by using its Streams feature, which captures data modification events in real-time. You can use this data to trigger real-time analytics or data pipelines.
How is DynamoDB different from other NoSQL databases?
DynamoDB is different from other NoSQL databases in several ways: it is fully managed, it provides a flexible data model with support for both document and key-value data, and it has a built-in integration with other AWS services.
How is data stored in DynamoDB?
Data in DynamoDB is stored in tables, which are similar to tables in a traditional relational database. Each table has a primary key, which must be unique across all items in the table.
What are the different data types supported by DynamoDB?
DynamoDB supports the following data types: number, string, binary, boolean, and null. It also supports complex data types such as lists, maps, and sets.
How does DynamoDB handle data durability and availability?
DynamoDB stores data across multiple facilities in an AWS region, and automatically replicates data to other regions for high availability and durability. It also has built-in features such as automatic backups and point-in-time recovery to ensure data integrity.
Can DynamoDB be used with other AWS services?
Yes, DynamoDB has built-in integrations with many other AWS services, such as Amazon S3, Amazon EMR, and AWS Lambda.
How is data queried in DynamoDB?
Data in DynamoDB is queried using the primary key or a secondary index. You can use the Query API to retrieve data using the primary key, or the GSI to query data using a secondary index.
What are secondary indexes in DynamoDB?
Secondary indexes in DynamoDB allow you to query data using an alternate key, other than the primary key. This can be useful for querying data in different ways, or for creating one-to-many relationships between tables.
Can DynamoDB trigger serverless functions?
Yes, DynamoDB has built-in support for triggering serverless functions using its Streams feature. You can set up a stream to capture data modification events in real-time, and then use that data to trigger a function
What are the differences between a primary key, partition key, and sort key in DynamoDB?
- Primary key: Uniquely identifies each item in a table. It can be a simple primary key (partition key) or a composite primary key (partition key and sort key).
- Partition key: The first part of a primary key, it determines the partition where the item is stored.
- Sort key: The second part of a composite primary key, it allows the items within a partition to be sorted for efficient querying.
What is a Global Secondary Index (GSI) and a Local Secondary Index (LSI)?
- GSI: A global secondary index is an index with a partition key and an optional sort key that can be different from the base table’s primary key. GSIs span all partitions and support eventually consistent reads by default, but can also support strongly consistent reads.
- LSI: A local secondary index is an index that has the same partition key as the base table, but a different sort key. LSIs are only available on tables with composite primary keys and support strongly consistent reads.
How does DynamoDB handle read and write consistency?
DynamoDB offers two types of read consistency: eventually consistent and strongly consistent. Eventually consistent reads provide better performance and availability, while strongly consistent reads guarantee that the read data reflects all writes that were successful up to a few seconds before the read request.
What is the difference between Provisioned Throughput and On-Demand Capacity modes in DynamoDB?
Provisioned Throughput is when you set specific read and write capacity units for your table or index, while On-Demand Capacity mode allows DynamoDB to automatically manage the capacity based on the actual request traffic. On-Demand Capacity mode can be more cost-effective for workloads with unpredictable or highly variable traffic patterns.
What is DynamoDB Streams?
DynamoDB Streams captures a time-ordered sequence of item-level modifications in a DynamoDB table and stores this data for up to 24 hours. You can use this data to build applications that react to changes in your table data or synchronize your table data with other data stores.
How do you secure data in DynamoDB?
DynamoDB provides various security mechanisms, such as AWS Identity and Access Management (IAM) for controlling access, encryption at rest using AWS Key Management Service (KMS) for data protection, and VPC endpoints for secure communication within your VPC.
What are the different backup and restore options available in DynamoDB?
DynamoDB offers two types of backups: on-demand backups and continuous backups with point-in-time recovery (PITR). On-demand backups allow you to create full backups of your table data and settings on demand, while PITR provides continuous backups of your table data, allowing you to restore your table to any point in time within the last 35 days.
How can you monitor and optimize the performance of DynamoDB?
You can monitor and optimize the performance of DynamoDB using the following approaches:
AWS Management Console: The console provides an overview of key performance metrics, such as read and write throughput, latency, and error rates.
Amazon CloudWatch: CloudWatch allows you to monitor and set alarms on various DynamoDB metrics, such as read and write capacity, consumed capacity, throttling events, and more.
AWS Trusted Advisor: Trusted Advisor can provide recommendations on cost optimization, security, fault tolerance, and performance improvement for your DynamoDB tables.
Query Optimization: Optimize your queries by choosing the right primary keys and indexes, using filter expressions, and limiting the number of items fetched.
Provisioned Throughput Management: Monitor your table’s consumed capacity and adjust the provisioned throughput accordingly to avoid throttling or over-provisioning. Consider using auto-scaling to manage capacity automatically.
DynamoDB Accelerator (DAX): DAX is a fully managed, in-memory cache for DynamoDB that can significantly improve read performance, reduce latency, and decrease the load on your base table. It’s particularly useful for read-heavy or bursty workloads.
Data Compression: Consider compressing large attribute values before storing them in DynamoDB to reduce storage costs and improve I/O efficiency.
Global Tables: Use global tables to replicate your table data across multiple AWS regions for low-latency access and improved data durability.
Time-to-Live (TTL): Set a TTL attribute on your items to automatically expire and delete old data, reducing storage costs and improving overall performance.
Backup and Restore: Regularly perform backups and test your restoration process to ensure data durability and recoverability.