Transactions Motivation
Case Study: Taylor Swift Concert Sales on Ticketmaster 🎤
The Scale of the Problem
What Went Wrong?
Concurrent Requests Broke the Site
- Cancelled tickets, reset to later in the day
- 5 hour wait times
- Bots took over the system
- Massive system failures under load
Why Study Taylor Swift Concert Sales?
Putting Scale in Perspective
🎤 Ticketmaster
System requests in a few hours
4x their previous record
Peak transactions/second (TPS): Not reported
💳 VISA Network
Transactions/day average
100K transactions/second at peak
Global payment processing
📦 Amazon Prime Day
DynamoDB requests/second
Sub-10ms response times
288B total transactions/day
On Complexity
🎤 Taylor Swift Tickets
Same seats, millions want them
- Limited inventory (same seats)
- Extreme contention
- Everyone wants exact same thing at same time
- Concentrated time/geography
💳 VISA Network
Global payments, strict consistency
- Financial regulations (zero tolerance)
- Cross-border coordination
- Real-time fraud detection
- 24/7 uptime requirements
📦 Amazon Prime Day
Different products
- Millions of unique items
- Low contention per item
- Distributed load naturally
- Predictable scaling patterns
🎵 Why Study This?
More fun than payment processing, more challenging than e-commerce, and exactly the kind of problem you'll face building the next generation of apps!
Why Study Transactions
🚀 The 100x Scale Revolution
🏦 Classic Era (1990s-2000s)
Banks, Walmart, Oracle
- Key Problems: Nightly batch processing, Regional scale
- Products: ATM networks, ERP systems
📱 My Era (2000s-2020s)
Gmail, Facebook, Instagram, Roblox
- Key Problems: Real-time updates, Global distribution
- Products: Social networks, Cloud services, Online gaming
🤖 Your Era (2030s+)
AI Agents, Neural interfaces, Autonomous systems
- Key Problems: Agent coordination, Quantum-scale transactions
- Products: Personal AI swarms, Global agent networks
⚡ Hardware Revolution
💾 2000s Hardware
HDDs, Single cores, MB RAM
Limited what you could build
⚡ 2020s Hardware
SSDs, Many cores, TB RAM
Enables anything my gen imagined!
🚀 2030s Hardware
Quantum storage, Neural chips, PB Memory
Enables what your gen imagines!
🧠 Data Structure Evolution Unlocks Scale
🌳 2000s: B-Trees
Oracle, DB2, SQL Server
- Key Problems: Disk-optimized reads, ACID guarantees
- Trade-offs: Slow writes, complex updates
📈 2020s: LSM Trees
Spanner, DynamoDB, RocksDB, Cassandra
- Key Problems: Write amplification, SSD optimization
- Trade-offs: Fast writes, eventual consistency
🧠 2030s: Neural (?) Trees
AI-Native DBs, Quantum stores, Learned indexes
- Key Problems: Self-optimization, Predictive caching
- Trade-offs: Intelligence vs energy, Learning overhead
💪 You're Building the Future
💡 You're entering the field at the perfect time!
Transaction processing is where the innovation and investment is heading. Master this now, lead the future.
🏃♂️ 1B Concurrent Users
Make Taylor Swift's 3.5M look like a warm-up
🎯 Perfect Consistency
Zero conflicts, zero data loss, zero compromises
🛡️ Instant Recovery
Self-healing systems that never go down
📈 Planetary Scale
Earth-spanning apps that work everywhere
What We'll Learn
Real-World Transaction Challenges
1️⃣ Concurrency
Millions of users trying to buy the same ticket
2️⃣ Consistency
Ensuring no double-bookings or lost sales
3️⃣ Availability
Keeping the system running under extreme load
4️⃣ Scalability
Handling 100x normal traffic spikes