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System Design

Anthropic Claude Opus 4.7 VS Google Gemini 2.5 Flash

Design a Scalable Concert Ticket Reservation System

Design a system for an online concert ticketing platform. Users can browse events, view seat availability, reserve specific seats for 10 minutes, pay through an external payment provider, and receive a digital ticket. The platform runs in one cloud region across multiple availability zones. Explicit constraints: 3 million registered users, 500,000 daily active users, major on-sale events can reach 150,000 concurrent users, peak load is 8,000 seat reservation attempts per second and 2,000 payment attempts per second, each event has up to 60,000 seats, the system must never sell the same seat twice, seat reservations expire after 10 minutes if unpaid, p95 latency for browsing and seat-map reads should be under 300 ms, p95 latency for reservation confirmation should be under 800 ms excluding payment-provider time, availability target during on-sale windows is 99.95%, recovery point objective is under 1 minute, recovery time objective is under 15 minutes, and payment provider callbacks are at-least-once, may arrive out of order, and may be delayed by up to 5 minutes. Provide a design plan. Include the main services and data stores, core APIs, data model for seats and reservations, request flow for browsing, reserving, paying, and expiring reservations, scaling strategy for traffic spikes, reliability and disaster recovery approach, consistency choices that prevent overselling, monitoring and alerting, and key trade-offs or alternatives you considered. State any reasonable assumptions you make.

389
May 19, 2026 09:49

Analysis

OpenAI GPT-5.5 VS Google Gemini 2.5 Flash

Choosing a Database for a Growing SaaS Startup

You are advising the CTO of a two-year-old B2B SaaS startup that provides project management software to mid-sized companies. The current setup uses a single PostgreSQL instance, and it is now showing strain: read queries on dashboards take 3–8 seconds during peak hours, the database is 800 GB and growing ~40 GB/month, and the team expects user count to triple over the next 12 months. The engineering team has 9 developers, only one of whom has significant database administration experience. Budget is constrained but not severely limited. The CTO is weighing four options: Vertically scale the existing PostgreSQL instance and add read replicas. Migrate to a managed distributed SQL database (e.g., CockroachDB or Spanner-like service). Split the workload: keep PostgreSQL for transactional data, introduce a separate analytical store (e.g., ClickHouse or BigQuery) for dashboards. Migrate to a NoSQL document database (e.g., MongoDB or DynamoDB). Write an analysis (roughly 500–800 words) that: Evaluates each of the four options against the startup's specific constraints (performance bottleneck location, team expertise, growth trajectory, budget). Identifies the key trade-offs and risks of each option. Reaches a clear, justified recommendation (you may recommend one option or a phased combination). Specifies what evidence or measurements you would want to verify before committing to the recommendation. Be concrete: refer to the numbers given, and avoid generic database advice that ignores the scenario.

478
May 16, 2026 09:38

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