This looks like a straightforward resume question until you realize they want actual numbers.
Select 2-3 databases that are most relevant to Discord's scale and real-time needs, and for each, structure your answer using a consistent framework: role, use case, scale, and operational responsibilities. Emphasize trade-offs you made and lessons learned, especially around high throughput, low latency, and data modeling.
Pro tip: Quantify scale with concrete numbers (e.g., '10K writes/sec', '5TB data') and tie operational work to business impact, like reducing latency by 30% or cutting costs by 20%. This shows you think like an owner, not just a user.
Pick 2-3 databases that align with Discord's tech stack (e.g., Cassandra, Redis, PostgreSQL, ScyllaDB) and your experience. Avoid listing every database you've touched; focus on depth over breadth.
For each database, state your level of involvement (e.g., primary developer, on-call, architect) and the specific use case (e.g., storing messages, caching, user profiles). Explain why that database was chosen over alternatives.
Provide concrete metrics: data volume (GB/TB), request throughput (QPS), latency requirements, and growth over time. If exact numbers are confidential, use ranges or relative terms (e.g., 'millions of writes per day').
Highlight hands-on work like schema design, query optimization, replication setup, backup/recovery, monitoring, and capacity planning. Mention specific tools and techniques you used.
Discuss challenges faced, trade-offs made (e.g., consistency vs. availability), and what you learned. This demonstrates deeper understanding and growth.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.