CLF-C02 Cloud Technology and Services Practice Question
A company wants to provide their data analysts with a way to run SQL queries on their S3 data lake using familiar BI tools like Tableau or Power BI. Which AWS service provides an ODBC/JDBC connection to S3 data?
⚠ Common exam trap
Many candidates confuse Amazon QuickSight (a visualization tool) with the query engine that provides the actual JDBC/ODBC connectivity, or think that AWS Glue Data Catalog alone enables SQL queries, when in fact Athena is the service that combines the Data Catalog with a serverless SQL engine and JDBC/ODBC support.
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
✓
Amazon Athena with JDBC/ODBC drivers
Amazon Athena is a serverless interactive query service that allows you to run standard SQL directly against data stored in Amazon S3. It provides JDBC and ODBC drivers that enable BI tools like Tableau and Power BI to connect to Athena and query the S3 data lake without needing to move or transform the data.
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 QuickSight
Why it's wrong here
Amazon QuickSight is a fully managed business intelligence and visualization service that can natively query Athena and other AWS data sources, but it is not a connectivity layer or a query driver. QuickSight exposes its own APIs and SPICE engine for analytics, and while it can consume Athena results, it does not provide JDBC/ODBC endpoints for third-party tools like Tableau to connect through. Therefore, selecting QuickSight would not give external BI tools the SQL-standard access they need to query S3 data directly.
- ✓
Amazon Athena with JDBC/ODBC drivers
Why this is correct
Amazon Athena is a serverless, interactive query service that runs standard SQL directly against data stored in Amazon S3. Athena provides official JDBC and ODBC drivers (from Simba) that enable BI tools like Tableau, Power BI, and QuickSight to connect to Athena as if it were a traditional database, using a preexisting connection string and standard SQL syntax. Because it is serverless, there are no clusters to provision or manage, and you pay only for the data scanned per query—making it the ideal choice for on-demand, low-latency SQL analytics over S3 data.
- ✗
Amazon EMR with Hive
Why it's wrong here
Amazon EMR with Hive can expose a HiveServer2 endpoint that supports JDBC and ODBC connections, and BI tools can indeed query data through it. However, EMR requires you to launch and manage a persistent or transient cluster, which introduces operational overhead, startup latency, and fixed infrastructure costs even when the cluster is idle. In contrast, Athena provides the same SQL-over-S3 capability without any cluster management, so EMR is not the simplest or most serverless answer for providing third-party BI connectivity to data in S3.
- ✗
AWS Glue Data Catalog only
Why it's wrong here
The AWS Glue Data Catalog is a centralized metadata repository that stores table definitions, schema information, locations, and partition details for data in S3 and other sources, but it is not a query execution engine and does not expose JDBC/ODBC endpoints. Athena is the component that actually runs SQL queries by using the Glue Data Catalog as its metastore, and it is Athena's JDBC/ODBC drivers that provide the standard SQL interface for BI tools. Thus, relying on the Glue Data Catalog alone would leave you with schema metadata but no way for Tableau or Power BI to issue SQL queries against S3 data.
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 |
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This CLF-C02 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 CLF-C02 exam.