Building for Speed: Our Tech Stack

The Goal

Financial operations need to be fast. When you're processing invoices, generating reports, or reconciling transactions, every second counts. We set an ambitious goal: sub-100ms response times for 99% of requests.

The Stack

We chose our stack based on three principles:

1. Type Safety - Catch errors at compile time, not in production
2. Performance - Handle millions of transactions without breaking a sweat
3. Developer Experience - Ship features quickly without sacrificing quality

Frontend

We use Next.js 15 with React for our web application:

• Server Components reduce bundle size and improve performance
• TypeScript catches errors before they reach production
• Tailwind CSS enables rapid UI development

Backend

Our API is built with Node.js and Golang:

• Node.js for business logic and API endpoints
• Golang for high-performance data processing
• PostgreSQL for transactional data
• Redis for caching and rate limiting

Performance Optimizations

Database Indexing

We use strategic indexes to keep queries fast:

-- Optimize invoice lookups
CREATE INDEX idx_invoices_customer_date
ON invoices(customer_id, created_at DESC);

-- Speed up reconciliation
CREATE INDEX idx_transactions_status_date
ON transactions(status, processed_at)
WHERE status = 'pending';

Caching Strategy

We implement multi-layer caching:

1. Browser Cache - Static assets and API responses
2. CDN Cache - Edge caching for global performance
3. Application Cache - Redis for frequently accessed data
4. Database Cache - PostgreSQL query cache

Async Processing

Heavy operations run in the background:

// Example: Process large reconciliation asynchronously
async function reconcileTransactions(accountId: string) {
  // Queue the job
  await queue.add("reconciliation", {
    accountId,
    priority: "high",
  });

  // Return immediately
  return { status: "queued" };
}

The Results

Our approach delivers:

• 50ms average API response time
• 99.9% uptime over the last 6 months
• 1M+ transactions processed daily

Benchmarks

| Operation | Response Time | Throughput | | --------------------- | ------------- | ---------- | | Create Invoice | 45ms | 2000/sec | | Generate Report | 120ms | 500/sec | | Reconcile Transaction | 35ms | 5000/sec |

Monitoring and Observability

We use Datadog for comprehensive monitoring:

• Real-time performance metrics
• Distributed tracing for debugging
• Custom dashboards for business metrics

Lessons Learned

What Worked

• Progressive Enhancement - Start simple, add complexity only when needed
• Automated Testing - Catch regressions before they hit production
• Feature Flags - Roll out changes gradually

What Didn't

• Premature Optimization - Focus on shipping first, optimize later
• Over-engineering - Simple solutions often outperform complex ones

What's Next

We're working on:

• GraphQL API for more flexible data fetching
• Webhooks for real-time event streaming
• Multi-region deployment for global performance

Want to build with us? We're hiring – check out oppulence.app/company for open positions.