- A
Use AWS Database Migration Service (DMS) with ongoing replication to S3
DMS supports CDC and can replicate changes to S3 with low latency.
- B
Use Amazon Kinesis Data Firehose with an Oracle JDBC connector
Why wrong: Firehose does not natively support Oracle as a source; custom solution needed.
- C
Use AWS Glue to perform a full table export daily
Why wrong: Full export does not provide near real-time CDC.
- D
Use AWS DataSync to sync the Oracle data files to S3
Why wrong: DataSync is for file systems, not databases.
Question 39 of 1,786
Using AWS DMS for Near Real-Time Change Data Capture from Oracle to S3
This DEA-C01 practice question tests your understanding of data ingestion and transformation. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company is building a data lake on S3 and needs to ingest data from on-premises Oracle database. The data is 5 TB and changes incrementally. The ingestion must capture changes in near real-time (less than 1 minute latency) and be cost-effective. Which approach should be used?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use AWS Database Migration Service (DMS) with ongoing replication to S3
AWS DMS with ongoing replication captures incremental changes from Oracle using its native change data capture (CDC) mechanism, such as Oracle LogMiner or binary logs, and streams them to S3 in near real-time with latency under 1 minute. This approach is cost-effective because DMS charges only for the compute resources used during replication, and S3 storage is inexpensive, making it ideal for a 5 TB dataset with continuous changes.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Use AWS Database Migration Service (DMS) with ongoing replication to S3
Why this is correct
DMS supports CDC and can replicate changes to S3 with low latency.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use Amazon Kinesis Data Firehose with an Oracle JDBC connector
Why it's wrong here
Firehose does not natively support Oracle as a source; custom solution needed.
- ✗
Use AWS Glue to perform a full table export daily
Why it's wrong here
Full export does not provide near real-time CDC.
- ✗
Use AWS DataSync to sync the Oracle data files to S3
Why it's wrong here
DataSync is for file systems, not databases.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse Kinesis Data Firehose's ability to accept data from custom sources with native JDBC support, leading them to choose Option B, but Firehose lacks built-in CDC connectors for relational databases like Oracle.
Detailed technical explanation
How to think about this question
DMS ongoing replication uses Oracle's LogMiner or direct binary log reading to capture changes as they occur, converting them into Apache Parquet or CSV format for S3 output, with a typical latency of seconds to a minute depending on transaction volume. Under the hood, DMS maintains a replication slot or log position to ensure exactly-once delivery, and it can handle schema evolution by mapping Oracle data types to S3 formats automatically. In a real-world scenario, if the Oracle database has high transaction rates (e.g., thousands of TPS), DMS can scale by increasing the replication instance size, whereas Firehose would require custom sharding and error handling.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
- →
Data Ingestion and Transformation — study guide chapter
Learn the concepts, then practise the questions
- →
Data Ingestion and Transformation practice questions
Targeted practice on this topic area only
- →
All DEA-C01 questions
1,786 questions across all exam domains
- →
AWS Certified Data Engineer Associate DEA-C01 study guide
Full concept coverage aligned to exam objectives
- →
DEA-C01 practice test guide
How to use practice tests most effectively before exam day
Related practice questions
Related DEA-C01 practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
Data Ingestion and Transformation practice questions
Practise DEA-C01 questions linked to Data Ingestion and Transformation.
Data Operations and Support practice questions
Practise DEA-C01 questions linked to Data Operations and Support.
Data Security and Governance practice questions
Practise DEA-C01 questions linked to Data Security and Governance.
Data Store Management practice questions
Practise DEA-C01 questions linked to Data Store Management.
DEA-C01 fundamentals practice questions
Practise DEA-C01 questions linked to DEA-C01 fundamentals.
DEA-C01 scenario practice questions
Practise DEA-C01 questions linked to DEA-C01 scenario.
DEA-C01 troubleshooting practice questions
Practise DEA-C01 questions linked to DEA-C01 troubleshooting.
Practice this exam
Start a free DEA-C01 practice session
Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.
FAQ
Questions learners often ask
What does this DEA-C01 question test?
Data Ingestion and Transformation — This question tests Data Ingestion and Transformation — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use AWS Database Migration Service (DMS) with ongoing replication to S3 — AWS DMS with ongoing replication captures incremental changes from Oracle using its native change data capture (CDC) mechanism, such as Oracle LogMiner or binary logs, and streams them to S3 in near real-time with latency under 1 minute. This approach is cost-effective because DMS charges only for the compute resources used during replication, and S3 storage is inexpensive, making it ideal for a 5 TB dataset with continuous changes.
What should I do if I get this DEA-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Keep practising
More DEA-C01 practice questions
- A data pipeline uses Kinesis Data Firehose to deliver streaming data to an S3 bucket. The data volume spikes occasionall…
- An e-commerce company uses AWS Glue to run ETL jobs that transform clickstream data from Amazon S3. The job reads Parque…
- A data engineering team uses Amazon Kinesis Data Analytics for Apache Flink to process streaming data. They notice that…
- A company uses AWS Glue to process streaming data from Amazon Kinesis Data Streams. The job reads JSON records and write…
- A data engineer applies the above bucket policy to an S3 bucket containing sensitive data. The goal is to allow only enc…
- A company uses AWS Glue to catalog data in Amazon S3. The security team requires that all sensitive data be identified a…
Last reviewed: Jul 4, 2026
This DEA-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DEA-C01 exam.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.