Consistent vs eventually consistent reads in DynamoDB - Interactive Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to perform a strongly consistent read in DynamoDB.

DynamoDB

response = table.get_item(Key={'id': '123'}, ConsistentRead=[1])

Drag options to blanks, or click blank then click option'

ATrue

BFalse

C'True'

D'False'

Attempts:

3 left

💡 Hint

Common Mistakes

Using string 'True' instead of boolean True

Setting ConsistentRead to False expecting strong consistency

Setting ConsistentRead=True ensures a strongly consistent read in DynamoDB.

2fill in blank

medium

Complete the code to perform an eventually consistent read in DynamoDB.

DynamoDB

response = table.get_item(Key={'id': '456'}, ConsistentRead=[1])

Drag options to blanks, or click blank then click option'

A'False'

BFalse

C'True'

DTrue

Attempts:

3 left

💡 Hint

Common Mistakes

Using string 'False' instead of boolean False

Setting ConsistentRead to True expecting eventual consistency

Setting ConsistentRead=False or omitting it performs an eventually consistent read.

3fill in blank

hard

Fix the error in the code to correctly request a consistent read.

DynamoDB

response = table.get_item(Key={'id': '789'}, ConsistentRead=[1])

Drag options to blanks, or click blank then click option'

A'true'

B'False'

CTrue

Dfalse

Attempts:

3 left

💡 Hint

Common Mistakes

Using lowercase or string values for ConsistentRead

Confusing string and boolean types

The ConsistentRead parameter must be a boolean True, not a string or lowercase.

4fill in blank

hard

Fill both blanks to perform a query with a consistent read.

DynamoDB

response = table.query(KeyConditionExpression=Key('userId').eq('user123'), [1]=[2])

Drag options to blanks, or click blank then click option'

AConsistentRead

BFilterExpression

CTrue

DFalse

Attempts:

3 left

💡 Hint

Common Mistakes

Using FilterExpression instead of ConsistentRead for consistency

Setting ConsistentRead to False expecting strong consistency

Use ConsistentRead=True to get a strongly consistent query result.

5fill in blank

hard

Fill all three blanks to create a strongly consistent scan with a filter expression.

DynamoDB

response = table.scan([1]=[2], [3]=Attr('status').eq('active'))

Drag options to blanks, or click blank then click option'

AConsistentRead

BTrue

CFilterExpression

DFalse

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing up FilterExpression and ConsistentRead parameters

Using False instead of True for ConsistentRead

Use ConsistentRead=True and FilterExpression to scan with strong consistency and filter results.

Practice

1. What is the main difference between consistent reads and eventually consistent reads in DynamoDB?

easy

A. Eventually consistent reads always return the latest data, consistent reads may return older data.

B. Consistent reads are faster than eventually consistent reads.

C. Consistent reads always return the latest data, eventually consistent reads may return older data.

D. There is no difference; both return the same data at the same speed.

Solution

1. Step 1: Understand consistent reads

   Consistent reads always return the most up-to-date data from DynamoDB.

2. Step 2: Understand eventually consistent reads

   Eventually consistent reads may return data that is slightly out of date but are faster and cheaper.

3. Final Answer:

   Consistent reads always return the latest data, eventually consistent reads may return older data. -> Option C

4. Quick Check:

   Consistent = latest data, Eventually consistent = possibly older data [OK]

Hint: Remember: consistent = latest, eventually consistent = maybe older [OK]

Common Mistakes:

• Thinking eventually consistent reads are always faster but not cheaper
• Confusing which read type returns the latest data
• Assuming both read types always return the same data

2. Which of the following is the correct way to specify a consistent read in a DynamoDB GetItem request using AWS SDK?

easy

A. "ConsistentRead": true

B. "ConsistentRead": false

C. "Consistent": true

D. "ReadConsistency": "strong"

Solution

1. Step 1: Recall DynamoDB GetItem syntax

   The parameter to request a consistent read is exactly "ConsistentRead" set to true or false.

2. Step 2: Identify correct syntax

   Only "ConsistentRead": true is valid; other options are incorrect parameter names or values.

3. Final Answer:

   "ConsistentRead": true -> Option A

4. Quick Check:

   Use "ConsistentRead": true for consistent reads [OK]

Hint: Look for exact parameter name "ConsistentRead" set to true [OK]

Common Mistakes:

• Using incorrect parameter names like "Consistent" or "ReadConsistency"
• Setting ConsistentRead to false to get consistent reads
• Confusing boolean values with strings

3. Consider this DynamoDB query snippet using AWS SDK for JavaScript:

const params = {
  TableName: "Users",
  Key: { "UserId": "123" },
  ConsistentRead: false
};
const data = await dynamoDb.get(params).promise();
console.log(data.Item.lastLogin);

What can you say about the freshness of the lastLogin value printed?

medium

A. It is guaranteed to be the most recent lastLogin value.

B. It will cause a runtime error because ConsistentRead must be true.

C. It will always be null because ConsistentRead is false.

D. It may be an older lastLogin value due to eventual consistency.

Solution

1. Step 1: Check ConsistentRead parameter

   ConsistentRead is set to false, meaning the read is eventually consistent.

2. Step 2: Understand impact on data freshness

   Eventually consistent reads may return stale data, so lastLogin might be older than the latest update.

3. Final Answer:

   It may be an older lastLogin value due to eventual consistency. -> Option D

4. Quick Check:

   ConsistentRead false = possibly stale data [OK]

Hint: ConsistentRead false means data may be stale [OK]

Common Mistakes:

• Assuming ConsistentRead false always returns latest data
• Thinking ConsistentRead false causes errors
• Believing data will be null if not consistent

4. You wrote this DynamoDB query but always get stale data even after updates:

const params = {
  TableName: "Orders",
  Key: { "OrderId": "789" },
  ConsistentRead: "true"
};
const result = await dynamoDb.get(params).promise();

What is the problem in this code?

medium

A. ConsistentRead must be omitted to get consistent reads.

B. ConsistentRead should be a boolean, not a string.

C. The Key attribute name is incorrect.

D. TableName should be lowercase.

Solution

1. Step 1: Check ConsistentRead data type

   ConsistentRead must be a boolean (true/false), not a string "true".

2. Step 2: Understand impact of wrong type

   Passing a string may cause DynamoDB to ignore the parameter, resulting in eventually consistent reads and stale data.

3. Final Answer:

   ConsistentRead should be a boolean, not a string. -> Option B

4. Quick Check:

   ConsistentRead must be boolean true/false [OK]

Hint: Use boolean true, not string "true" for ConsistentRead [OK]

Common Mistakes:

• Passing ConsistentRead as string instead of boolean
• Changing Key attribute name unnecessarily
• Thinking TableName case matters for consistency

5. You have a high-traffic app that shows user profiles updated frequently. You want to minimize latency but ensure users see their latest profile changes immediately after saving. Which read strategy should you use in DynamoDB?

hard

A. Use consistent reads only for profile fetches immediately after updates, eventually consistent otherwise.

B. Use eventually consistent reads everywhere to reduce cost and latency.

C. Use consistent reads for all profile fetches regardless of timing.

D. Use eventually consistent reads only for profile fetches immediately after updates.

Solution

1. Step 1: Understand trade-offs

   Consistent reads ensure latest data but cost more and have higher latency; eventually consistent reads are cheaper and faster but may be stale.

2. Step 2: Apply strategy for user experience

   Use consistent reads right after updates to show fresh data, then eventually consistent reads for normal fetches to save cost and improve speed.

3. Final Answer:

   Use consistent reads only for profile fetches immediately after updates, eventually consistent otherwise. -> Option A

4. Quick Check:

   Consistent reads after update, eventually consistent otherwise [OK]

Hint: Use consistent reads only when fresh data is critical [OK]

Common Mistakes:

• Using consistent reads everywhere causing high cost and latency
• Using eventually consistent reads immediately after updates causing stale data
• Ignoring cost and latency trade-offs