MCQs on Advanced Features and Integrations | DynamoDB MCQ Question & Answer
Elevate your expertise in AWS DynamoDB with these 30 multiple-choice questions (MCQs) focusing on advanced features and integrations. Learn about DynamoDB Streams, TTL for data expiry, ACID transactions, backup and recovery, and DAX for caching. These AWS DynamoDB MCQ questions and answers are perfect for mastering this NoSQL database’s real-world applications and preparing for exams.
Chapter 5: Advanced Features and Integrations
1. DynamoDB Streams: Real-Time Data Processing
- What is the primary purpose of DynamoDB Streams?
a. To trigger backups
b. To log query history
c. To enable real-time data processing
d. To increase storage capacity - How long are DynamoDB Streams records retained by default?
a. 7 days
b. 24 hours
c. 48 hours
d. 3 days - Which AWS service can be integrated with DynamoDB Streams for processing changes?
a. AWS Lambda
b. Amazon S3
c. AWS CloudFormation
d. Amazon RDS - What is a key feature of a stream-enabled DynamoDB table?
a. Provides point-in-time recovery
b. Tracks all data changes in the table
c. Automatically archives deleted items
d. Enables high write throughput - Which operation can trigger a DynamoDB Stream?
a. Data retrieval
b. Table deletion
c. Data modification
d. Read operation
2. TTL (Time to Live) for Data Expiry
- What does the TTL feature in DynamoDB do?
a. Enables point-in-time recovery
b. Deletes expired items automatically
c. Enhances query speed
d. Creates automatic backups - How is the expiration time for items set in DynamoDB TTL?
a. By using a predefined timestamp attribute
b. By assigning a priority level
c. By setting an auto-delete policy
d. By specifying an event trigger - Which format is used for TTL expiration values?
a. ISO 8601
b. UNIX epoch time
c. UTC string
d. Local timezone - What happens to expired items in a DynamoDB table?
a. They are deleted automatically in the background
b. They are marked as archived
c. They generate a DynamoDB Stream event
d. They are stored in a backup - Why should TTL be used in DynamoDB?
a. To reduce storage costs
b. To improve read throughput
c. To enhance item replication
d. To simplify query operations
3. Transactions: ACID Support in DynamoDB
- What is a key benefit of using transactions in DynamoDB?
a. Enables eventual consistency
b. Guarantees ACID properties
c. Improves table scaling
d. Increases data retention - How many operations can be included in a single DynamoDB transaction?
a. Up to 10
b. Up to 20
c. Unlimited
d. Up to 5 - Which DynamoDB SDK method is used to write transactional items?
a. BatchWriteItem
b. TransactWriteItems
c. PutItem
d. UpdateItem - What happens if one operation in a DynamoDB transaction fails?
a. Only the failing operation is rolled back
b. The entire transaction is rolled back
c. The successful operations are retained
d. The transaction is retried automatically - Which of the following is an example of a DynamoDB transaction use case?
a. Read-heavy applications
b. Real-time analytics
c. Multi-item update consistency
d. Large-scale data migrations
4. Backup and Restore, Point-In-Time Recovery
- What does DynamoDB Point-In-Time Recovery (PITR) allow you to do?
a. Automatically scale tables
b. Restore data to a previous state
c. Archive data indefinitely
d. Schedule automatic exports - What is the retention period for PITR in DynamoDB?
a. 35 days
b. 7 days
c. 24 hours
d. 14 days - How are backups created in DynamoDB?
a. Through manual API calls or AWS Management Console
b. Automatically triggered after table creation
c. As part of a TTL policy
d. Using CloudFormation templates - What type of backups does DynamoDB provide?
a. Incremental backups only
b. Full table backups
c. Selective backups
d. Query-specific backups - Which of the following is a limitation of DynamoDB on-demand backups?
a. Cannot back up tables larger than 1 TB
b. Only available for on-demand tables
c. Does not support global tables
d. Does not restore indexes
5. DynamoDB Accelerator (DAX) for Caching
- What is the purpose of DynamoDB Accelerator (DAX)?
a. To enhance query speed with in-memory caching
b. To replicate tables across regions
c. To enable automatic backups
d. To store query logs - How does DAX improve application performance?
a. By reducing the number of write operations
b. By caching frequently accessed data
c. By scaling read capacity units automatically
d. By minimizing TTL expiration delays - Which API calls are accelerated by DAX?
a. Write-heavy operations
b. All read operations
c. Query and GetItem calls
d. Backup and Restore operations - Which feature is unique to DAX?
a. Allows asynchronous query execution
b. Provides single-digit millisecond latency
c. Supports unlimited caching size
d. Enables data encryption - What is required to integrate DAX with a DynamoDB application?
a. Updating the DynamoDB SDK to support DAX
b. Creating a global secondary index
c. Enabling TTL on all items
d. Configuring DynamoDB Streams - What happens if an item is not found in the DAX cache?
a. The application throws an error
b. The request is automatically forwarded to DynamoDB
c. The cache is refreshed from a backup
d. The operation is retried - How can DAX reduce costs for read-heavy applications?
a. By replacing DynamoDB tables with DAX clusters
b. By reducing read capacity unit (RCU) consumption
c. By automatically deleting expired data
d. By enabling write operation optimization - Which DynamoDB API operation is not supported by DAX?
a. BatchGetItem
b. Query
c. Scan
d. TransactWriteItems - What is a potential limitation of DAX?
a. Does not support on-demand tables
b. Limited to specific AWS regions
c. Requires additional configuration for encryption
d. Inconsistent performance for write-heavy workloads - How does DAX handle eventual consistency?
a. By maintaining a write-through cache
b. By providing strongly consistent reads only
c. By ensuring immediate replication
d. By relying on eventual consistency of DynamoDB
Answer Key
| QNo | Answer |
|---|---|
| 1 | c. To enable real-time data processing |
| 2 | b. 24 hours |
| 3 | a. AWS Lambda |
| 4 | b. Tracks all data changes in the table |
| 5 | c. Data modification |
| 6 | b. Deletes expired items automatically |
| 7 | a. By using a predefined timestamp attribute |
| 8 | b. UNIX epoch time |
| 9 | a. They are deleted automatically in the background |
| 10 | a. To reduce storage costs |
| 11 | b. Guarantees ACID properties |
| 12 | a. Up to 10 |
| 13 | b. TransactWriteItems |
| 14 | b. The entire transaction is rolled back |
| 15 | c. Multi-item update consistency |
| 16 | b. Restore data to a previous state |
| 17 | a. 35 days |
| 18 | a. Through manual API calls or AWS Management Console |
| 19 | b. Full table backups |
| 20 | d. Does not restore indexes |
| 21 | a. To enhance query speed with in-memory caching |
| 22 | b. By caching frequently accessed data |
| 23 | c. Query and GetItem calls |
| 24 | b. Provides single-digit millisecond latency |
| 25 | a. Updating the DynamoDB SDK to support DAX |
| 26 | b. The request is automatically forwarded to DynamoDB |
| 27 | b. By reducing read capacity unit (RCU) consumption |
| 28 | d. TransactWriteItems |
| 29 | d. Inconsistent performance for write-heavy workloads |