AWS Glue for SaaS Data Ingestion via JDBC — ETL Transformation
A company needs to ingest data from multiple SaaS applications (e.g., Salesforce, Marketo) into Amazon S3 for centralized analytics. The data volume is several GB per day. Which AWS service is most suitable for this ingestion?
Quick Answer
The answer is AWS Glue, as it is the most suitable service for batch ingestion of SaaS data via JDBC into Amazon S3. Glue’s ETL jobs can natively connect to JDBC sources like Salesforce and Marketo, extract several GB of data per day, and transform it before landing it in S3 for centralized analytics. On the AWS Certified Data Engineer Associate DEA-C01 exam, this question tests your ability to distinguish between batch ingestion tools (Glue) and query-only or streaming services; a common trap is choosing Athena for its query speed or Kinesis for real-time needs, but neither handles scheduled JDBC batch loads. Remember that Glue’s crawlers and JDBC support make it the go-to for SaaS-to-S3 pipelines. Memory tip: “Glue sticks batch JDBC to S3.”
⚠ Common exam trap
Many exam-takers confuse AWS Glue with a data catalog or transformation-only service, overlooking its robust ETL ingestion capabilities with native SaaS connectors, and mistakenly choose Kinesis Data Firehose because it 'ingests' data, but it lacks the necessary source integrations for batch SaaS extraction.
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
✓
AWS Glue
AWS Glue is the most suitable service because it provides a fully managed ETL (Extract, Transform, Load) capability with built-in connectors for SaaS applications like Salesforce and Marketo. Glue can extract data from these sources, transform it as needed, and write it to Amazon S3, handling the several GB per day volume efficiently without requiring custom code for each source.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Amazon Kinesis Data Firehose
Why it's wrong here
Firehose is for streaming data, not batch ingestion from SaaS.
- ✓
AWS Glue
Why this is correct
Glue can connect to SaaS sources via JDBC and perform ETL to S3.
- ✗
Amazon Athena
Why it's wrong here
Athena is a query service, not for ingestion.
- ✗
AWS Data Pipeline
Why it's wrong here
Data Pipeline is an older service; Glue is more modern and suitable.
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 |
Go deeper
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Same concept, more angles
1 more way this is tested on DEA-C01
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Variation 1. A company needs to ingest data from multiple SaaS applications (Salesforce, Marketo) and load it into Amazon Redshift. The data must be transformed before loading. Which AWS service should be used to build the ingestion pipelines?
easy- A.AWS Database Migration Service (DMS)
- B.AWS Data Pipeline
- C.Amazon AppFlow
- ✓ D.AWS Glue (crawlers and ETL jobs)
Why D: AWS Glue is the correct choice because it provides a fully managed ETL service that can connect to various data sources (including SaaS applications via JDBC or custom connectors), transform the data using Apache Spark or Python scripts, and load it into Amazon Redshift. Glue crawlers can catalog the source schemas, and Glue ETL jobs handle the transformation logic required before loading into Redshift, making it ideal for building ingestion pipelines from multiple SaaS sources.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.