← Glossary / Data Feed Subscription

What is Data Feed Subscription?

A data feed subscription is a delivery model where scraped data is continuously pushed to a client's storage sink — S3, Snowflake, or a webhook — on a predefined schedule. Instead of managing infrastructure, proxies, and selector maintenance, data teams consume a clean, versioned schema as a service. When target sites change their DOM or tighten anti-bot thresholds, the extraction layer absorbs the shock, ensuring downstream analytics models never ingest a silent null.

Data DeliveryETLSchema VersioningS3 / SnowflakeManaged Service
// 02 — definitions

Pipelines as
a service.

The shift from owning scraping infrastructure to consuming structured data on a schedule, and why it changes the unit economics of data engineering.

Ask a DataFlirt engineer →

TL;DR

A data feed subscription abstracts away the chaos of web scraping. You define the target, the schema, and the cadence (e.g., daily at 00:00 UTC). The provider handles proxy rotation, headless browser fleets, and selector repairs, delivering a validated dataset directly to your cloud bucket. It turns unpredictable infrastructure costs into a predictable operational expense.

01Definition & structure
A data feed subscription is an arrangement where a data provider continuously scrapes, cleans, and delivers structured data from specific web targets to a client. Instead of the client writing code, managing proxies, and dealing with anti-bot blocks, they simply define the required schema, the target URLs, and the delivery cadence. The output is typically pushed directly into a data lake (like S3) or a data warehouse (like Snowflake) in an analytics-ready format like Parquet or JSONL.
02Delivery cadences
Feeds operate on schedules dictated by the business need and the target's update frequency. Common cadences include:
  • Daily/Weekly Batch: Standard for product catalogs, real estate listings, and public directories.
  • Hourly Micro-batch: Used for dynamic pricing, news aggregation, and inventory monitoring.
  • Event-Driven: Triggered by specific market events rather than a strict clock.
The cadence directly impacts the compute cost and the proxy bandwidth required to maintain the feed.
03Schema contracts and validation
The defining feature of a production-grade data feed is the schema contract. Web data is inherently messy; target sites change layouts without warning. A feed subscription places a validation layer between the raw extraction and the client delivery. If a target site changes its price format from a number to an image, the validation layer catches the type coercion failure, halts the delivery of corrupted data, and alerts the provider to fix the extractor.
04How DataFlirt handles it
We treat data feeds as mission-critical infrastructure. Our extraction fleet runs continuously, pulling data into our internal raw zone. We apply strict schema validation, deduplication, and normalisation before writing the final Parquet files to your S3 bucket. If a target site deploys a new anti-bot measure, our automated systems rotate the proxy pool and adjust browser fingerprints. You pay for the delivered data, not the compute cycles we spend fighting Cloudflare.
05The true cost of self-hosting
Many teams start by building their own scrapers, assuming the cost is just the AWS EC2 bill. The hidden cost is maintenance. Target sites change their DOM, proxies get banned, and anti-bot systems evolve. A self-hosted pipeline requires constant engineering attention to keep the data flowing. A feed subscription shifts this maintenance burden entirely to the provider, freeing your data engineers to focus on analytics and modeling rather than fixing regex patterns.
// 03 — the economics

What does a
feed cost?

Pricing a managed feed involves calculating the compute required to bypass anti-bot systems, the frequency of extraction, and the maintenance overhead of the target's DOM volatility.

Total Cost of Ownership (In-House) = TCO = infra_cost + (eng_hours × rate) + proxy_spend
Engineering time spent fixing broken selectors usually eclipses raw compute costs. Data Engineering Economics
DataFlirt Feed Pricing = Price = base_tier + (records × compute_multiplier)
Flat monthly fee based on volume and target anti-bot complexity. DataFlirt Pricing Model
Data Freshness = Freshness = Tdelivery − Textraction
The delta between when a record was scraped and when it hits your warehouse. Pipeline SLOs
// 04 — feed execution trace

From target DOM
to Snowflake table.

A live trace of a daily B2B pricing feed. The pipeline extracts the data, validates it against a strict schema contract, and pushes the Parquet file to the client's S3 bucket.

ParquetSchema ValidationS3 Push
edge.dataflirt.io — live
CAPTURED
// feed execution: daily pricing catalog
feed.id: "sub-b2b-pricing-092"
target: "https://example-distributor.com/catalog"

// extraction phase
workers.active: 120
records.extracted: 48,291
anti_bot.blocks: 14 // auto-retried with new residential IPs

// validation phase
schema.version: "v2.4"
validation.pass: 48,289
validation.fail: 2 // quarantined due to type coercion error

// delivery phase
sink.type: "s3"
sink.path: "s3://client-bucket/pricing/2026-10-24.parquet"
delivery.status: 200 OK
webhook.trigger: success // dbt model triggered
// 05 — feed disruptions

Why self-hosted
feeds fail silently.

The most common reasons an in-house data feed delivers garbage data. In a managed subscription, these failure modes are absorbed by the provider's SLA.

PIPELINES MONITORED ·   300+ active
AVG UPTIME ·  ·  ·  ·  ·  99.9%
UPDATED ·  ·  ·  ·  ·  ·  2026-05-19
01

Selector drift (DOM changes)

silent failure · Site redesigns break CSS/XPath targeting
02

Anti-bot threshold changes

hard block · Cloudflare/DataDome updates trigger 403s
03

Type coercion errors

schema break · Price string changes format (e.g., 'Call for price')
04

Pagination loop failures

data loss · Crawler stops early due to UI changes
05

Target server timeouts

partial run · Target infrastructure cannot handle crawl concurrency
// 06 — delivery architecture

Zero-maintenance data,

pushed directly to your warehouse.

DataFlirt's feed architecture separates extraction from delivery. We extract into our raw zone, run strict schema validation, and only push to your S3 bucket or Snowflake instance once the dataset passes completeness checks. If a target site pushes a redesign at 2 AM, our monitors catch the drop in field density, quarantine the run, and page our engineers. You never wake up to an empty table or a broken downstream dashboard.

feed-delivery.log

Live status of a managed data feed pushing to a client's Snowflake instance.

feed.status activeok
schema.contract strict validationenforced
delivery.sink snowflake_aws
cadence hourly
last_run.completeness 0.998ok
last_run.quarantined 12 recordsreview pending
sla.uptime 99.9%met

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// 07 — FAQ

Common
questions.

Common questions about managed data feeds, schema contracts, delivery formats, and how DataFlirt handles target site volatility.

Ask us directly →
What is the difference between an API and a Data Feed? +
An API is a pull mechanism — you request data on-demand, and the system fetches it in real-time. A Data Feed is a push mechanism — data is extracted in batches on a schedule and delivered to your storage. Feeds are vastly more efficient for large-scale analytics, catalog monitoring, and machine learning ingestion.
How do you handle schema changes when the target site updates? +
We use versioned data contracts. If a target site changes its DOM and a field goes missing, our extraction layer flags the completeness drop and quarantines the run. Our engineers patch the selector, backfill the missing data, and push the complete file. Your downstream systems never receive a broken schema.
Can I get real-time data through a feed subscription? +
We support micro-batching down to 5-minute intervals for high-priority targets (like spot pricing or inventory monitoring). However, if you need sub-second latency for individual records, you should use our real-time Scraping API instead of a feed.
What delivery formats and destinations do you support? +
We deliver in JSONL, Parquet, CSV, or Avro. Destinations include AWS S3, Google Cloud Storage, Azure Blob, Snowflake, BigQuery, or direct POST to a custom webhook. Parquet to S3 is our recommended standard for analytical workloads.
Who owns the data delivered in the feed? +
You do. DataFlirt operates the pipeline and manages the infrastructure, but the extracted dataset delivered to your sink is entirely yours. We do not resell your custom feed data to competitors.
How does DataFlirt price feed subscriptions? +
Pricing is a flat monthly fee based on two factors: the volume of records extracted per month, and the anti-bot complexity of the target site. You don't pay for retries, proxy bandwidth, or the engineering hours we spend fixing broken selectors.
$ dataflirt scope --new-project --target=data-feed-subscription READY

Tell us what
to extract.
We do the rest.

20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue dump or a continuous feed across millions of records — we scope, build, and operate the pipeline.

Start a pipeline → View pricing
hello@dataflirt.com  ·  Bengaluru  ·  IST  ·  typical reply < 4h
// 08 — keep reading

Related glossary terms

Data Delivery

Managed Data Feed

The operational model where a provider handles the end-to-end scraping pipeline for you.

Read →
Data Delivery

Data as a Service (DaaS)

Consuming structured web data as a product rather than building the extraction infrastructure.

Read →
Data Delivery

Delta File Delivery

Delivering only the records that have changed since the last feed execution.

Read →
Data Engineering

Data Contract

The strict schema agreement that ensures a data feed won't break downstream analytics.

Read →