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AWS Database SpecialtyDBS-C01AWS Databases18 min read

How to Pass AWS Database Specialty (DBS-C01): Complete Study Guide

Complete study guide for the AWS Database Specialty (DBS-C01) exam. Covers all domains, key database services, migration strategies, and performance tuning tips.

Last updated February 7, 2026

The AWS Certified Database - Specialty (DBS-C01) validates your ability to recommend, design, and maintain optimal AWS database solutions. If you work with databases on AWS or want to specialize in data architecture, this certification sets you apart.

With an estimated pass rate of 42-52%, the Database Specialty is not easy. But if you understand the AWS database landscape and can match the right database to the right use case, you are well on your way.

This guide covers every domain, all the key services, migration strategies, and the performance tuning concepts you need to pass.

Exam Overview

DetailInformation
Exam CodeDBS-C01
LevelSpecialty
Cost$300 (or $150 with voucher)
Duration180 minutes
Questions65 questions
Passing Score750 / 1000
FormatMultiple choice and multiple response
PrerequisiteNone (but database experience recommended)

Recommended experience: AWS recommends at least 5 years of database experience and 2 years of hands-on AWS database experience. Having Solutions Architect Associate helps significantly.

Exam Domains and Weights

DomainWeight
Workload-Specific Database Design26%
Deployment and Migration20%
Management and Operations18%
Monitoring and Troubleshooting18%
Database Security18%

The heaviest domain is workload-specific database design at 26%. This means knowing which database service to use for which scenario is the most tested skill.

AWS Database Services: The Complete Map

This is the foundation of the entire exam. You need to know every AWS database service, what it does, and when to choose it over alternatives.

Relational Databases

Amazon RDS (Relational Database Service)

EngineKey Characteristics
MySQLOpen source, widely supported, good for web applications
PostgreSQLOpen source, advanced features, JSON support, GIS extensions
MariaDBMySQL-compatible, community-driven
OracleEnterprise, licensing options (bring your own or included)
SQL ServerMicrosoft ecosystem, Windows integration

Key RDS concepts to master:

  • Multi-AZ deployments (synchronous replication for high availability)
  • Read replicas (asynchronous replication for read scaling)
  • Automated backups and point-in-time recovery
  • Storage types: General Purpose (gp3), Provisioned IOPS (io1/io2)
  • RDS Proxy for connection pooling
  • Parameter groups and option groups
  • Encryption at rest and in transit
  • Performance Insights for monitoring

Amazon Aurora

Aurora gets its own section because it appears heavily on the exam:

  • MySQL and PostgreSQL compatible
  • Up to 5x throughput of MySQL, 3x of PostgreSQL
  • Storage auto-scales up to 128 TB
  • 6 copies of data across 3 AZs
  • Aurora Replicas (up to 15, with automatic failover)
  • Aurora Global Database for cross-region replication
  • Aurora Serverless v2 for variable workloads
  • Aurora Backtrack for point-in-time recovery without restore
  • Aurora Cloning for fast database copies

When to choose Aurora over standard RDS:

  • Need higher availability (6-way replication)
  • Need more read replicas (15 vs 5)
  • Need serverless scaling
  • Need cross-region with sub-second replication
  • Performance is critical for MySQL/PostgreSQL workloads

NoSQL Databases

Amazon DynamoDB

DynamoDB questions make up a significant portion of the exam:

ConceptWhat to Know
Partition keyPrimary key - determines data distribution
Sort keyOptional - enables range queries within a partition
GSI (Global Secondary Index)Alternate partition/sort key, eventually consistent
LSI (Local Secondary Index)Same partition key, different sort key, strongly consistent
Capacity modesOn-demand vs provisioned (know when to use each)
DynamoDB StreamsChange data capture for event-driven architectures
DAXIn-memory caching layer for microsecond reads
Global TablesMulti-region, multi-active replication
TTLAutomatic item expiration
TransactionsACID transactions across items and tables

DynamoDB design patterns (heavily tested):

  • Single-table design for related entities
  • Hot partition avoidance (choosing good partition keys)
  • Write sharding for high-throughput scenarios
  • Sparse indexes for selective queries
  • Overloading sort keys for flexible access patterns

Amazon DocumentDB

  • MongoDB-compatible document database
  • Managed by AWS (not actual MongoDB)
  • When to use: MongoDB workloads that need AWS-managed service
  • Supports MongoDB 3.6, 4.0, and 5.0 compatibility

Amazon Keyspaces

  • Apache Cassandra-compatible
  • Serverless, pay-per-request
  • When to use: Cassandra workloads that need a managed service

In-Memory Databases

Amazon ElastiCache

EngineBest For
RedisCaching, session management, real-time analytics, pub/sub, sorted sets
MemcachedSimple caching, multi-threaded performance

Key concepts:

  • Cluster mode enabled vs disabled (Redis)
  • Replication groups for high availability
  • Cache strategies: lazy loading, write-through, TTL-based
  • When to use ElastiCache vs DAX (DynamoDB-specific)

Amazon MemoryDB for Redis

  • Redis-compatible with durability
  • When to use: Need Redis as a primary database (not just cache)
  • Multi-AZ with transaction log for durability

Purpose-Built Databases

Amazon Redshift (Data Warehouse)

  • Columnar storage for analytics
  • Massively parallel processing (MPP)
  • Redshift Spectrum for querying S3 data
  • Concurrency scaling for burst workloads
  • Distribution styles: KEY, EVEN, ALL, AUTO
  • Sort keys: compound and interleaved
  • Materialized views for query optimization
  • AQUA for accelerated queries

Amazon Neptune (Graph Database)

  • Property graph (Gremlin) and RDF (SPARQL)
  • When to use: Social networks, fraud detection, knowledge graphs, recommendation engines
  • Neptune ML for graph-based predictions

Amazon QLDB (Quantum Ledger Database)

  • Immutable, cryptographically verifiable transaction log
  • When to use: Audit trails, supply chain, financial transactions
  • NOT a blockchain (centralized, owned by AWS)

Amazon Timestream

  • Purpose-built for time series data
  • When to use: IoT data, application monitoring, DevOps metrics
  • Automatic tiering between memory and magnetic storage

Database Migration Strategies

Migration is 20% of the exam. Know these services and strategies:

AWS Database Migration Service (DMS)

FeatureDetails
Homogeneous migrationSame engine to same engine (Oracle to RDS Oracle)
Heterogeneous migrationDifferent engines (Oracle to Aurora PostgreSQL)
Continuous replicationCDC (Change Data Capture) for ongoing sync
Schema conversionAWS SCT for schema/code conversion

AWS Schema Conversion Tool (SCT):

  • Converts database schemas between engines
  • Identifies code that cannot be automatically converted
  • Generates migration assessment reports
  • Handles stored procedures, functions, triggers

Migration Patterns

The 6 Rs for database migration:

  1. Rehost - Lift and shift to EC2 (self-managed)
  2. Replatform - Move to RDS (managed, same engine)
  3. Repurchase - Switch to a different product
  4. Refactor - Re-architect for a new engine (e.g., Oracle to Aurora)
  5. Retire - Decommission
  6. Retain - Keep on-premises

Key migration scenarios tested:

  • Oracle to Aurora PostgreSQL (heterogeneous, requires SCT + DMS)
  • On-premises MySQL to RDS MySQL (homogeneous, DMS only)
  • Cassandra to DynamoDB (application-level changes needed)
  • MongoDB to DocumentDB (DMS supported)

Performance Tuning: What the Exam Tests

RDS/Aurora Performance

  • Read replicas for read-heavy workloads
  • RDS Proxy for connection management and pooling
  • Performance Insights for identifying bottlenecks
  • Storage optimization: move from gp2 to gp3, or to io1/io2 for IOPS
  • Parameter group tuning for engine-specific optimization
  • Query optimization through explain plans and slow query logs

DynamoDB Performance

  • Partition key design is the number one performance factor
  • DAX for microsecond read latency
  • On-demand vs provisioned capacity based on traffic patterns
  • GSIs and LSIs for efficient query patterns
  • Batch operations for bulk reads/writes
  • TTL for automatic cleanup of expired data

Redshift Performance

  • Distribution keys for minimizing data movement
  • Sort keys for faster range queries
  • Compression encoding for storage optimization
  • VACUUM and ANALYZE for table maintenance
  • Concurrency scaling for handling burst query loads
  • Materialized views for caching complex queries

Database Security (18% of Exam)

Encryption

DatabaseAt RestIn Transit
RDS/AuroraKMS encryption, TDE for Oracle/SQL ServerSSL/TLS
DynamoDBKMS encryption (AWS owned, AWS managed, or CMK)TLS (always on)
RedshiftKMS or HSM encryptionSSL
ElastiCacheKMS encryption (Redis only)TLS (Redis only)
NeptuneKMS encryptionSSL

Access Control

  • IAM authentication for RDS (MySQL, PostgreSQL), DynamoDB, Neptune
  • Database-native authentication for RDS, Redshift
  • VPC security groups for network-level access control
  • Secrets Manager for credential rotation
  • RDS Proxy with IAM authentication for Lambda connections

Audit and Compliance

  • RDS audit logs - database engine-specific logging
  • Aurora advanced auditing - granular activity logging
  • DynamoDB Streams - change data capture
  • CloudTrail - API call logging for all database services
  • AWS Config - configuration compliance tracking

Study Plan: 8-10 Weeks

Weeks 1-2: Assessment and Database Fundamentals

  • Take a gap assessment to identify your starting point
  • Review relational database concepts (normalization, indexing, ACID)
  • Review NoSQL concepts (partition keys, eventual consistency, CAP theorem)
  • Read the official DBS-C01 exam guide

Weeks 3-4: Relational Databases Deep Dive

  • RDS configuration, Multi-AZ, read replicas
  • Aurora architecture, Global Database, Serverless v2
  • Redshift architecture, distribution styles, sort keys
  • Hands-on: Create RDS instances, configure replicas, test failover

Weeks 5-6: NoSQL and Purpose-Built Databases

  • DynamoDB table design, capacity modes, indexes, streams
  • ElastiCache patterns, replication, eviction policies
  • Neptune, QLDB, Timestream, DocumentDB, Keyspaces
  • Hands-on: Design DynamoDB tables, implement caching patterns

Weeks 7-8: Migration and Operations

  • DMS configuration and replication tasks
  • SCT for schema conversion
  • Migration patterns and decision frameworks
  • Backup strategies, maintenance windows, monitoring
  • Performance Insights, CloudWatch metrics, troubleshooting

Weeks 9-10: Security, Practice, and Review

  • Encryption patterns for each database service
  • IAM authentication vs database authentication
  • Network security (VPCs, security groups, endpoints)
  • Full-length practice exams (timed)
  • Review all wrong answers thoroughly
  • Final practice exam 2-3 days before the real exam

Exam Strategy Tips

1. Always Start With "What Type of Workload Is This?"

The exam constantly tests your ability to match workloads to databases:

Workload TypeBest Database
Transactional (OLTP)RDS, Aurora, DynamoDB
Analytical (OLAP)Redshift
Key-value / high throughputDynamoDB
Document storageDocumentDB
Graph relationshipsNeptune
Time seriesTimestream
Immutable ledgerQLDB
CachingElastiCache
Session managementElastiCache Redis, DynamoDB
Real-time leaderboardsElastiCache Redis

2. Know When Aurora Beats Standard RDS

Aurora is AWS's preferred managed relational database. If a question asks for high availability, performance, or scalability with MySQL/PostgreSQL, Aurora is usually the answer.

3. DynamoDB Design is Critical

You will see multiple questions on DynamoDB table design. Practice:

  • Choosing partition keys that distribute data evenly
  • Designing sort keys for flexible queries
  • Using GSIs and LSIs appropriately
  • Understanding on-demand vs provisioned capacity tradeoffs

4. Read Questions Carefully for Key Words

  • "Minimal operational overhead" = managed service (Aurora/DynamoDB over EC2 databases)
  • "Most cost-effective" = right-size, consider serverless
  • "Fastest migration" = homogeneous with DMS
  • "Near-zero downtime migration" = DMS with CDC
  • "Immutable audit trail" = QLDB

Frequently Asked Questions

How hard is the AWS Database Specialty exam?

The AWS Database Specialty (DBS-C01) has an estimated pass rate of 42-52%. It requires deep knowledge of AWS database services, migration strategies, and performance tuning. Most successful candidates have 2+ years of hands-on AWS database experience and study for 8-10 weeks.

Do I need DBA experience for the Database Specialty?

Traditional DBA experience helps but is not strictly required. You need to understand relational and NoSQL database concepts, migration strategies, and AWS-specific database services. Cloud architects and developers who work regularly with databases can pass with focused preparation.

Which AWS database service is most tested on DBS-C01?

DynamoDB and Aurora/RDS are the most heavily tested services. DynamoDB questions focus on table design, partition keys, and capacity modes. Aurora questions focus on architecture, replication, and when to choose Aurora over standard RDS. Together, these services make up roughly 40-50% of exam content.

How is the Database Specialty different from Solutions Architect?

Solutions Architect tests broad AWS knowledge across all services. Database Specialty goes deep into database-specific topics: table design, query optimization, migration strategies, database-level security, and performance tuning. It requires understanding database internals, not just which service to use.

The Bottom Line

The AWS Database Specialty validates expertise that organizations desperately need. As data grows exponentially, professionals who can design, migrate, and optimize database solutions on AWS are in high demand.

The key to passing is understanding the AWS database landscape at a deep level. Know when to use each service, how to migrate between them, how to optimize performance, and how to secure them properly.

Do not try to memorize facts. Understand the reasoning behind database decisions. When you can explain WHY Aurora is better than standard RDS for a specific workload, or WHY DynamoDB needs a certain partition key design, you are ready.

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