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Study Timeline

How Long to Study for AWS Database Specialty

A complete week-by-week study plan for the AWS Database Specialty (Hard difficulty, ~50% pass rate).

10

Weeks

9

Hrs/Week

92

Total Hours

~50%

Pass Rate

Establish the current target before studying anything
Week 1

6-8 hours this week

  • Confirm that DBS-C01 is retired by reading the AWS Training and Certification blog post published January 30, 2024
  • Download the AWS Certified Data Engineer - Associate exam guide from the AWS certification page and compare its domains with the DBS-C01 domains preserved below
  • Check your AWS Certification Account under Exam History if you already hold DBS-C01, and note the exact three-year expiry date
  • Decide between AWS Certified Data Engineer - Associate at 150 USD and AWS Certified Solutions Architect - Associate at 150 USD based on the job you want
  • Take the free AWS Certification Official Practice Question Set for your chosen live exam to set a baseline
Relational databases on AWS: RDS and Aurora
Week 2

8-10 hours this week

  • Read the Amazon RDS User Guide sections on Multi-AZ deployments, read replicas and automated backups
  • Launch an Aurora MySQL cluster with a reader endpoint and observe failover behaviour by triggering a failover manually
  • Compare an Aurora cluster volume with RDS storage in the Aurora User Guide storage and reliability section
  • Configure parameter groups and option groups on an RDS instance and note which parameters require a reboot
  • Enable Performance Insights and generate load, then read the database load chart by wait event
DynamoDB and NoSQL design
Week 3

8-10 hours this week

  • Work through the DynamoDB Developer Guide chapter on best practices for designing partition keys
  • Build a single table with a global secondary index and a local secondary index and query both
  • Switch a table between on-demand and provisioned capacity and compare the CloudWatch consumed capacity metrics
  • Deliberately create a hot partition, observe throttling, and read how adaptive capacity responds
  • Put DynamoDB Accelerator in front of the table and measure the latency difference
Purpose-built engines
Week 4

8-10 hours this week

  • Read the service overview pages for Amazon DocumentDB, Amazon Neptune, Amazon Keyspaces, Amazon Timestream and Amazon QLDB
  • Write a one-paragraph rule for each engine stating the workload shape that makes it the right answer
  • Deploy an ElastiCache for Redis cluster and implement a cache-aside pattern against an RDS instance
  • Load a small graph into Neptune and run a Gremlin traversal to see what graph queries actually look like
  • Compare Amazon Redshift with Aurora for an analytical query on the same dataset
Migration with AWS DMS and AWS SCT
Week 5

9-11 hours this week

  • Read the AWS Database Migration Service User Guide sections on full load, change data capture, and task settings
  • Run a homogeneous migration from a source MySQL instance to Amazon RDS for MySQL using AWS DMS
  • Run a heterogeneous migration using AWS SCT to convert an Oracle or SQL Server schema to PostgreSQL
  • Break the migration on purpose with an unreachable endpoint and read the DMS task logs to diagnose it
  • Validate a completed load with the AWS DMS data validation feature and reconcile the results
Backup, restore and disaster recovery
Week 6

8-10 hours this week

  • Perform a point-in-time restore of an RDS instance and note the new endpoint that results
  • Copy an encrypted snapshot to a second Region and work through the KMS key requirements
  • Configure DynamoDB point-in-time recovery and on-demand backups, then restore to a new table
  • Set up AWS Backup with a backup plan covering RDS and DynamoDB and apply a retention rule
  • Write recovery point objective and recovery time objective figures for each approach you tested
Database security and access control
Week 7

8-10 hours this week

  • Enable IAM database authentication on an RDS PostgreSQL instance and connect using a generated auth token
  • Enforce TLS by setting rds.force_ssl and confirm that a plaintext connection is refused
  • Create a customer managed KMS key, encrypt a new RDS instance with it, and test cross-account snapshot sharing
  • Enable database audit logging and export it to CloudWatch Logs, then query it with Logs Insights
  • Store a database credential in AWS Secrets Manager with automatic rotation and update an application to read it
Monitoring, troubleshooting and cost
Week 8

8-10 hours this week

  • Build a CloudWatch dashboard covering CPU, freeable memory, storage, connections and replica lag for one RDS instance
  • Create alarms with SNS notification for storage below a threshold and replica lag above a threshold
  • Diagnose a slow query using Performance Insights, then fix it with an index and measure the change
  • Model the monthly cost of the same workload on Aurora, RDS and DynamoDB using the AWS Pricing Calculator
  • Review AWS Trusted Advisor checks relating to idle and underutilised database instances
Data engineering topics the retired exam did not cover
Week 9

9-11 hours this week

  • Read the AWS Glue Developer Guide sections on crawlers, the Data Catalog and ETL jobs
  • Build a small pipeline that lands data in Amazon S3, catalogues it with Glue and queries it with Amazon Athena
  • Read about Amazon Kinesis Data Streams and Amazon Data Firehose for streaming ingestion
  • Work through data quality and lineage concepts in the Data Engineer - Associate exam guide
  • Take the AWS Certification Official Practice Question Set for Data Engineer - Associate again and compare with your week one baseline
Timed practice on a live exam
Week 10

10-12 hours this week

  • Take the AWS Certification Official Pretest for your chosen live exam under timed conditions
  • Rebuild each missed question into a single sentence stating why the correct service won
  • Review the list of AWS service short names available through the Help button during the exam
  • Re-read the appendix of your chosen exam guide and delete out-of-scope services from revision
  • Book the exam and claim the 50 percent discount voucher in your AWS Certification Account if you already hold an AWS certification
Working Full-Time Schedule

Duration: 15 weeks

Hours/week: 6 hours

Daily: ~1 hours on weeknights

Weekends: 3-4 hours Saturday + Sunday

Study during lunch breaks and commute time. Use weekends for deeper study sessions and practice tests.

Weekend-Only Schedule

Duration: 20 weeks

Hours/week: 5 hours

Saturday: 4-5 hours of focused study

Sunday: 3-4 hours of practice tests

Longer timeline but sustainable. Review flashcards on weeknights for 15-20 minutes to maintain retention.

Frequently Asked Questions

How long does it take to study for the AWS Database Specialty?

Plan for 10 weeks of dedicated study at 9 hours per week (92 total hours). If studying while working full-time, extend to 15 weeks.

Can I pass the AWS Database Specialty in 2 weeks?

It's unlikely for most candidates. The AWS Database Specialty is rated "Hard" difficulty and typically requires 10 weeks of preparation. Rushing increases your risk of failing and paying the exam fee again.

How many hours a day should I study for AWS Database Specialty?

Aim for 2-2 hours per day on weekdays. Quality matters more than quantity, use active recall and practice tests rather than passive reading.

Is AWS Database Specialty hard to pass?

The AWS Database Specialty is rated "Hard" difficulty with a pass rate of ~50%. Solid preparation over several months is recommended.

Ready to start your AWS Database Specialty journey?

Get the complete exam guide with tips, resources, and practice questions.

View AWS Database Specialty Guide