Question 1

What is polyglot persistence, and when would you recommend adopting this approach? What are the key benefits and challenges of using multiple database technologies within a single organization?

Accepted Answer

Polyglot persistence is the practice of using different database technologies for different data storage needs within an organization or even within a single application. Rather than forcing all data into one database type, you choose the best tool for each specific use case, leveraging the unique strengths of different database engines.

The rationale behind polyglot persistence is that no single database technology excels at everything. A relational database like PostgreSQL is excellent for structured transactional data with complex relationships and strong consistency requirements. A docu

Question 2

Explain the CAP theorem and its practical implications for database architecture decisions. How do modern distributed databases navigate the trade-offs described by CAP?

Accepted Answer

The CAP theorem, formulated by Eric Brewer, states that a distributed data system can provide at most two of three guarantees simultaneously: Consistency, where every read receives the most recent write; Availability, where every request receives a response; and Partition tolerance, where the system continues operating despite network partitions between nodes. Since network partitions are inevitable in distributed systems, the practical choice is between consistency and availability during a partition event.

It is important to understand that CAP is about behavior during partitions, not dur

Question 3

Explain database sharding and the different sharding strategies available. How do you choose the right shard key, and what are the consequences of a poor choice?

Accepted Answer

Database sharding is a horizontal scaling strategy that distributes data across multiple independent database instances, called shards, to handle workloads that exceed the capacity of a single server. Each shard holds a subset of the total data, and together they form the complete dataset. Sharding enables a database to scale write throughput, storage capacity, and query performance beyond what vertical scaling can achieve.

There are several sharding strategies, each with distinct characteristics. Range-based sharding divides data by ranges of the shard key value. For example, customers wit

Question 4

What is table partitioning, and how does it differ from sharding? Describe the main partitioning types and when you would apply each one to improve performance at scale.

Accepted Answer

Table partitioning divides a single logical table into multiple physical segments called partitions, all managed within the same database instance. Unlike sharding, which distributes data across multiple database servers, partitioning organizes data within a single server to improve query performance, simplify maintenance, and enable efficient data lifecycle management.

The key distinction is that partitioning is transparent to the application. Queries against the partitioned table work exactly as they would against a non-partitioned table. The database engine automatically directs queries

Question 5

What are the primary approaches to database migration, and how do you decide between lift-and-shift, re-platforming, and refactoring? What factors influence the decision for each approach?

Accepted Answer

Database migration approaches range from simple moves to complete redesigns, and choosing the right approach depends on balancing business goals, technical requirements, timeline, and available resources. Understanding the spectrum of options helps ensure you invest the right level of effort for each migration.

Lift-and-shift, also called rehosting, moves the database to a new environment with minimal changes. You take the existing database and move it to new hardware, a different data center, or a cloud-hosted virtual machine running the same database engine. The schema, data, stored proce

Question 6

Explain how AWS Database Migration Service works and when you would use it. What are its capabilities and limitations for different migration scenarios?

Accepted Answer

AWS Database Migration Service is a managed service that helps migrate databases to AWS quickly and securely while the source database remains fully operational during the migration. It supports both homogeneous migrations like MySQL to MySQL and heterogeneous migrations like Oracle to PostgreSQL, making it versatile for many migration scenarios.

DMS works by creating a replication instance, which is a managed EC2 instance that runs the migration software. You define source and target endpoints specifying connection details for each database. A migration task defines what data to migrate an

Question 7

What is database capacity planning, and what key metrics do you track to forecast future resource needs? How far ahead should you plan, and what triggers a capacity review?

Accepted Answer

Database capacity planning is the process of forecasting future resource requirements based on current usage trends, known business changes, and growth projections. The goal is to ensure that database infrastructure can handle upcoming demand without over-provisioning resources that waste money. Effective capacity planning prevents both emergency scaling events and unnecessary spending.

The key metrics I track fall into four categories: compute, memory, storage, and throughput. For compute, I monitor CPU utilization during peak and average periods, tracking the trend over weeks and months.

Question 8

How do you determine whether a database instance is right-sized? What indicators suggest over-provisioning or under-provisioning, and how do you adjust without impacting performance?

Accepted Answer

Right-sizing is the practice of matching database instance resources to actual workload requirements. Both over-provisioning and under-provisioning are problematic. Over-provisioning wastes money on unused capacity, which at scale can represent thousands of dollars monthly per instance. Under-provisioning causes performance degradation, user-facing latency, and potential outages.

Indicators of over-provisioning include consistently low CPU utilization during peak hours, typically below 20 percent averaged over the peak period across several weeks. Memory utilization that never approaches th

Question 9

How do you establish and maintain database standards across an organization? What standards are most important, and how do you ensure adoption without creating bureaucratic overhead?

Accepted Answer

Database standards create consistency that makes systems maintainable, debuggable, and operable at scale. Without standards, every database becomes a unique snowflake requiring individual knowledge to manage. However, standards must be practical and adopted willingly rather than imposed as bureaucratic constraints.

I prioritize standards in three tiers based on their impact. The first tier covers standards that prevent incidents and data loss. These are mandatory and non-negotiable. They include backup and recovery procedures with verified restore testing, security standards for authenticat

Question 10

Describe an effective database change management process. How do you balance the need for control and safety with the need for development velocity and agility?

Accepted Answer

Database change management must protect production data integrity while enabling teams to deliver changes quickly. The traditional DBA gatekeeper model where every change requires manual DBA review creates a bottleneck that frustrates development teams. The opposite extreme, where developers deploy database changes directly to production without review, leads to outages from untested migrations. The right process provides guardrails that catch dangerous changes while allowing routine changes to flow quickly.

I implement a risk-based approval process. Changes are classified by risk level bas

Database Administrator

Topics

Database Architecture & Strategy

Large-Scale Database Operations

Database Migration & Modernization

Capacity Planning & Cost Optimization

Database Team Leadership & Governance

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