99.9% Uptime SLA
10M+ Products Daily
24/7 Real-time Sync
SUCCESS STORY
Enterprise Data Pipeline

We Built a Pipeline That Processes10 Million Products Daily

See how we engineered an industrial-grade price aggregation system that extracts data from Amazon, Walmart, eBay + 17 more retailers with 99.9% reliability and real-time API delivery.

"This pipeline transformed our pricing strategy. We now track competitor prices in real-time across 20+ platforms."

Michael Chen

VP of Data, Fortune 500 Retailer

Powered By Enterprise Tech Stack

OpenSearchAWS S3DockerKubernetesPythonREST API
System Overview
PROD-US-EAST-1
Amazon
3.2M
Walmart
2.8M
eBay
2.1M
AutoZone
2.6M
Scrapers
PipelineJSONL
StorageAPI
Latency
47ms
Throughput
125/sec
Error Rate
0.01%

Infrastructure

50
K8s Pods
JSONL
Pipeline
REST
API

Live Activity Stream

[10:23:45] ✓ Scraped batch #45,231 (2,341 items)
[10:23:44] → Processing Samsung 65" QLED TV
[10:23:43] ⚡ API: 2,341 req/s (avg 87ms)
[10:23:42] 📦 S3: Archived 10GB to bucket

Results Delivered

312% ROI in 3 Months

THE PROBLEM

You're Losing $47,000/month Because Your
Competitors Update Prices 73x Faster

Your dev team quoted you $2.3M and 18 months to build what we deliver in 7 days for $8,500/month

Here's Exactly What We Do

  • Deploy 127 concurrent scrapers across 50+ Kubernetes pods

  • Extract from Amazon, Walmart, eBay + 17 retailers simultaneously

  • Deliver via sub-100ms API with 99.9% uptime SLA

  • Update your prices every 6 hours (not every 6 weeks)

The Math That Matters

Revenue lost to slow pricing:-$47,000/mo
In-house build cost:-$127,000/mo
Our solution:$8,500/mo
You save:$165,500/mo

That's $1.98M saved annually

Our Guarantee

10M products scraped in week 1

or 100% money back

Never had to give a refund in 4 years

AG

AutoParts Giant

$2.3B Annual Revenue

Before

Manual price updates every 3 weeks

After (Day 7)

Automated updates every 6 hours

Result

+$1.7M/month

Additional profit from dynamic pricing

Live System Metrics

10.7M

Products/Day

47ms

API Response

$8.5K

Total Cost/Mo

127

Active Scrapers

Activity Stream

Scraped: iPhone 15 Pro - $999 (Amazon)
Indexed: 1,247 products → OpenSearch
API: Served 2,341 requests (87ms avg)
Queue: 45,231 products pending

What Others Charge

Accenture
$2.3M setup18 months
IBM
$127K/month12 months
In-house
$89K/monthForever
Cognilium
$8,500/mo48 hours
⏰

While You're Reading This:

  • Your competitor just updated 47,000 prices
  • You lost 3 customers to better pricing
  • Amazon changed 1,247 prices in your category

Every day you wait = $1,566 lost

Ready to Scrape 10 Million Products?

See our live pipeline in action and get started in 7 days

⚠️ Only taking 2 more clients this quarter

Engineering Challenge

From Web Scraping toIndustrial-Grade ETL

Transforming ordinary web scraping into a massive concurrent data pipeline capable of processingmillions of products daily

Single-threaded scraping
10M+ products/day pipeline
10M+
Products Daily
20+
Retail Giants
99.9%
Uptime SLA
<100ms
API Response

The Challenge

Enterprise-scale data extraction

🏪
Extract pricing data from 20+ retail giants
Amazon, Walmart, eBay, Auto parts stores
📊
Process 10M+ SKUs daily
Real-time price updates
⚡
Handle concurrent extraction
Massive scale operations
🔄
Auto-resume on failures
High availability guarantee
🚀
Serve thousands of users
Scalable API infrastructure
Traditional approach would take
6+ months
Just for basic implementation

Our Solution

Industrial-grade architecture

🔄
Concurrent scrapers
Python + aiohttp
Intelligent proxy pool rotation
📍
Offset-tracking system
Redis + PostgreSQL
Auto-resume capabilities
🚰
JSONL streaming pipelines
Apache Kafka
Efficient data processing
⚡
OpenSearch deployment
Elasticsearch cluster
High-speed indexed search
☁️
Multi-cloud scaling
Hetzner + AWS
50+ containers orchestration
Delivered in just
6 weeks
From concept to production
Enterprise Architecture

Industrial-ScaleData Pipeline Architecture

A battle-tested, enterprise-grade system processing10M+ products daily with99.9% uptime guarantee

50+
Concurrent Workers
6 hrs
Full Refresh
99.9%
Uptime SLA
<100ms
API Response
01
🏪

Multi-Source Ingestion

20+ retail giants including Amazon, Walmart, eBay

TECH STACK
PythonaiohttpProxies
Rate limiting
Retry logic
Failover protection
02
⚡

Concurrent Processing

Horizontally scaled extraction with intelligent queuing

TECH STACK
KubernetesRedisLoad Balancing
Auto-scaling
Dead letter queues
Circuit breakers
03
🚰

Stream Processing

JSONL pipelines with real-time data validation

TECH STACK
Apache KafkaSchema RegistryAvro
Data deduplication
Schema evolution
Backpressure handling
04
🚀

High-Speed APIs

OpenSearch indexing with S3 archival and CDN

TECH STACK
OpenSearchS3CloudFront
Sub-100ms queries
Auto-indexing
Global CDN

Why This Architecture Wins

💰
87% Cost Reduction
vs traditional ETL solutions
⚡
10x Faster Processing
compared to sequential scraping
🛡️
Zero Data Loss
with automatic failover & recovery
📈
Infinite Scalability
auto-scales to any data volume
🔒
Enterprise Security
SOC2 compliant infrastructure

Ready to Scale Your Data Pipeline?

Get this exact architecture implemented for your business. From concept to production in just 6 weeks.

⚡ Implementation starts Monday

4 engineers available this week

Similar system generated $2.4M in additional revenue in first 6 months

Auto parts e-commerce client

Delivered Results

An industrial-grade ETL stack optimized for AI training, dashboards, and pricing tools

Daily Processing

  • 10M+ products scraped
  • Price & stock updates
  • Ratings & reviews sync

Technical Excellence

  • High concurrency design
  • Auto-resume on failures
  • Intelligent failover

Business Value

  • AI training datasets
  • Real-time pricing tools
  • Analytics dashboards

Technology Stack

Python
OpenSearch
AWS S3
Docker
Kubernetes
Hetzner
JSONL
REST API
Proxy Pools
Queue Systems
Load Balancer
Monitoring

Why Choose Cognilium for Data Engineering

We don't just build data pipelines - we architect industrial-scale solutions that handle enterprise complexity

Enterprise Scale Engineering

Built systems handling 10M+ daily operations across Fortune 500 companies. We understand enterprise requirements, not just startup MVPs.

  • 99.9% uptime SLA compliance
  • Sub-100ms API response times
  • Horizontal scaling architecture

Deep Technical Expertise

Our engineers have built data systems at Apple, Google, and Microsoft. We bring Silicon Valley expertise to your engineering challenges.

  • Advanced concurrency patterns
  • Real-time streaming architectures
  • Custom ML pipeline optimization

Rapid Implementation

While your competitors spend 18 months building, we deliver production-ready systems in weeks. Time-to-market is everything.

  • Pre-built framework components
  • Battle-tested infrastructure patterns
  • Immediate scaling from day one
CAPABILITY SHOWCASE

We Built This 10M+ Daily Scraper.
We Can Build Similar For You.

This price aggregator demonstrates our ability to architect industrial-scale data engineering solutions. Your business deserves the same level of technical excellence.

Production-Ready Code

Enterprise-grade systems built for 99.9% uptime and horizontal scaling

Weeks, Not Months

Rapid implementation using battle-tested frameworks and patterns

Dedicated Team

Senior engineers who've built similar systems at Fortune 500 companies