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Real-Time Scraping

Real-Time Scraping

We build event-driven data pipelines that push updates the moment they appear. Our real-time scraping solution combines websocket monitoring, change detection algorithms, and Webhooks delivery to ensure you never work with stale data. In fast-moving markets, latency matters—we optimize for sub-second detection.

Technical Architecture

Real-time detection requires multiple strategies. For sites with WebSocket connections or Server-Sent Events, we maintain persistent connections with automatic reconnection. For polling-based detection, we implement adaptive intervals based on target change frequency—some sources get checked every few seconds, others hourly. Our change detection uses content hashing with perceptual diff algorithms to catch visual changes even when DOM structure shifts. The orchestrator routes detected changes through message queues with at-least-once delivery guarantees.

Pro-Tip: We implement "change prediction" using historical patterns—if a site typically updates at 9 AM EST, we increase polling frequency during those windows to catch changes faster.

Data Quality & Validation

Real-time doesn’t mean sloppy. Every change event validates against Pydantic schemas before delivery. Duplicate detection uses content hashing with temporal clustering to avoid sending the same update multiple times. For sites that rapidly toggle states (price flashing, availability changes), we implement hysteresis—requiring sustained state for N seconds before triggering alerts. Deduplication runs at both the event and content levels.

Anti-Bot Strategy

Frequent requests trigger aggressive anti-bot measures. We implement IP Rotation with longer rotation cycles during high-frequency monitoring. Stealth Plugins ensure every request appears from a unique browser session. For sites using User Behavior Analytics , we vary interaction timing and navigation patterns to avoid pattern detection. Residential proxies provide authentic ISP contexts that survive longer under scrutiny.

Compliance & Ethical Standards

High-frequency monitoring must respect target infrastructure. We implement polite rate floors that prevent request flooding even during critical monitoring windows. For commercial data, we ensure our monitoring doesn’t impact target site performance—a key ethical consideration. GDPR and DPDP Act 2023 compliance extends to real-time data—any personal data detected in real-time streams gets immediately masked or excluded from delivery.


Cost Savings

30-50%

reduce missed opportunity costs
Speed to Market

< 5 sec

detection-to-delivery latency
Accuracy

99.9%

change detection rate

Frequently Asked Questions

Sub-second for WebSocket/SSE sources. For polling sources, we adapt interval based on target sensitivity—typically 5-30 seconds for high-priority sources. Our average detection-to-delivery latency is under 5 seconds.

We deliver via [Webhooks](/wiki/webhooks/) to any HTTP endpoint, stream to Kafka/PubSub topics, push to AWS SQS/SNS, or write directly to your database. Webhook delivery includes retry logic with exponential backoff.

Yes. We implement targeted field monitoring using [XPath](/wiki/xpath/) or [CSS Selectors](/wiki/css-selector/) to watch specific elements. Only field-level changes trigger events, reducing noise and processing overhead.

We implement change magnitude thresholds and hysteresis. Minor fluctuations (price changes < 1%, timestamp updates) get filtered. Only sustained changes above configurable thresholds trigger alerts.

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