Client
US-based Enterprise Data Provider
Scalable API Data Aggregation Platform Enterprise Backend Case Study
A unified data aggregation platform engineered to fetch, normalize, and synchronize high-volume data from multiple APIs built for enterprise scale, automation, and real-time analytics readiness.
Project Snapshot
Industry
Data Analytics , SaaS , Enterprise
Service Category
· Backend Engineering, Data Engineering
Tech Stack
Python, Node.js, REST APIs, AWS Lambda, AWS RDS, Redis
Duration
5 Months
Scale
12+ API providers · 10M+ records processed daily
Status
Live (Multi-agency deployment)
About This Platform
The client needed a centralized, high-performance data aggregation system capable of ingesting data from numerous external APIs, normalizing formats, and making aggregated datasets available to internal dashboards and partner systems.
Inexture built a fully automated, cloud-native ingestion engine optimized for speed, reliability, and large-volume data processing.
Client Requirements
- Centralize API ingestion for all third-party providers
- Normalize inconsistent response structures
- Add retry, throttling & failover mechanisms
- Automate data sync with scheduled jobs
- Optimize database for large-scale read/write operations
- Provide secure APIs for internal consumption
- Support onboarding of new API sources without downtime
Challenges We Solved
- Fragmented API structures: pagination, limits & auth differences
- Rapidly growing data volume requiring scalable infra
- No unified storage or retrieval model
- Frequent provider downtime requiring resilient retry logic
- Need for 24×7 ingestion with zero failures
- Heavy queries requiring indexing, partitioning & caching
Data Ingestion & Transformation Flow Diagram
This flow explains how raw provider responses move through throttling, retries, normalization, deduplication, and storage – supporting 10M+ records daily.
Our Solution & Architecture
We built a cloud-native, modular, auto-scaling ingestion ecosystem designed for high-volume API aggregation.
- Modular ingestion microservices (one per provider)
- Unified normalization engine to align all JSON schemas
- Retry + exponential backoff for rate-limited or failing APIs
- High-frequency CRON/Lambda schedulers for real-time ingestion
- Optimized database with partitioning & deduplication logic
- Secure internal APIs exposing aggregated datasets
- Redis caching layer for high-speed analytics & downstream APIs
- AWS-based autoscaling for continuous performance
Scalable API Platform - Infrastructure Architecture
An infrastructure view of cloud components, queues, schedulers, databases, caching, and monitoring built for high-frequency ingestion and enterprise reliability.
Technology Stack
A robust and scalable technology foundation powering seamless performance and future-ready growth
- Python (FastAPI)
- Node.js
- Cron Workers
- REST APIs
- Webhooks
- Lambda Functions
- Async Queues
- PostgreSQL
- MySQL
- DynamoDB
- AWS Lambda
- Redis Cache
- AWS RDS
- CloudWatch Logs
- CI/CD
What We Achieved
Business Impact showcases how our solutions translate into measurable results and real business value.
We focus on improving efficiency, accelerating growth, and delivering lasting competitive advantage.
- 10M+ records processed daily with 99.98% accuracy
- Sync speed improved from 2 hours → 3 minutes
- 98% reduction in manual data processing
- 12+ external APIs unified into one system
- 40% faster internal reporting due to normalized data
- Fully secure, audit-ready, cloud-native ecosystem
Industries We Serve
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Speak with our engineering team to build scalable ingestion engines, secure APIs, and enterprise-ready backend systems tailored to your organization.
