← Glossary / Managed Data Feed

What is Managed Data Feed?

Managed data feed is an end-to-end data delivery model where a vendor handles the entire scraping lifecycle — target discovery, anti-bot bypass, extraction, schema validation, and delivery — providing the buyer with a clean, structured dataset on a guaranteed schedule. Instead of buying software or proxies to build your own pipeline, you buy the output. It shifts the operational risk of site changes and blockades entirely to the provider.

Data DeliveryDaaSSLAETLZero-Maintenance

// 02 — definitions

Buy the data,
not the software.

The shift from operating scraping infrastructure to consuming guaranteed datasets, and why enterprise teams prefer SLAs over raw proxies.

Ask a DataFlirt engineer →

TL;DR

A managed data feed abstracts away the chaos of web scraping. You define the target and the schema; the provider delivers the data to your S3 bucket or Snowflake instance. If the target site redesigns its DOM or deploys Cloudflare, the provider fixes it before your next delivery window.

01Definition & structure

A managed data feed is a service where a data provider takes full responsibility for extracting data from a target website and delivering it to the client in a structured format. The client specifies the target URLs, the required fields (the schema), and the delivery cadence. The provider handles the proxies, the headless browsers, the anti-bot bypass, the parsing logic, and the maintenance.

02How it works in practice

Once the feed is configured, the provider's infrastructure runs the extraction jobs on the agreed schedule. The raw HTML is parsed, transformed into the agreed schema, and validated. If the data passes validation, it is serialized into the requested format (e.g., Parquet or JSONL) and pushed to the client's storage bucket (e.g., AWS S3). A webhook is often fired to notify the client's ETL pipeline that new data is ready for ingestion.

03The value of shifting operational risk

Web scraping is inherently brittle. Target sites change their DOM, deploy new Cloudflare challenges, or block proxy subnets without warning. When you build your own scrapers, your engineering team absorbs this maintenance burden. A managed feed shifts this risk to the provider. You pay for the SLA; the provider pays the engineering cost of keeping the pipeline alive.

04How DataFlirt handles it

We treat managed feeds as strict data contracts. Every record extracted by our fleet is validated against a versioned schema before it ever reaches your bucket. If a target site updates and a critical field drops, our pipeline quarantines the run and alerts our engineers. We fix the selector and backfill the data, ensuring that your downstream analytics and machine learning models are never poisoned by malformed records.

05The "build vs. buy" misconception

Many teams assume building a scraper in-house is cheaper because the initial script takes a weekend to write. They fail to account for the total cost of ownership (TCO): proxy bandwidth, anti-detect browser compute, and the endless hours spent fixing broken selectors. At enterprise scale, buying a managed feed is almost always cheaper than dedicating full-time engineers to scraper maintenance.

// 03 — the SLA math

How we measure
feed reliability.

A managed feed is only as good as its guarantees. DataFlirt monitors every pipeline against strict Service Level Agreements covering freshness, completeness, and schema adherence.

Delivery Reliability = (successful_deliveries / scheduled_deliveries) × 100

Target > 99.9% uptime per month across all active feeds. DataFlirt SLA standard

Data Freshness = T_delivery − T_extraction

Time from edge capture to client bucket. DataFlirt median is < 90s. Pipeline telemetry

Schema Adherence = 1 − (records_failing_validation / total_records)

Must be 1.0. Invalid records are quarantined, never delivered. Extraction validation layer

// 04 — delivery trace

From extraction
to client bucket.

A live trace of a daily managed data feed delivering real estate listings to a client's AWS S3 bucket, including schema validation and webhook notification.

S3 deliveryschema validationwebhook

edge.dataflirt.io — live

CAPTURED

// job initialization
job.id: "feed-re-uk-daily-042"
target: "rightmove-uk-sales"
records.extracted: 142,850

// schema validation
schema.contract: "v4.2"
validation.pass: 142,848
validation.fail: 2 // quarantined: missing price

// payload generation
format: "parquet"
compression: "snappy"
file.size: "18.4 MB"

// delivery
destination: "s3://client-prod-data/rightmove/2026-05-19/"
upload.status: 200 OK
webhook.trigger: "https://api.client.com/ingest/notify"
webhook.status: 202 Accepted
pipeline.status: COMPLETED

// 05 — operational risks

What breaks
unmanaged pipelines.

When you build it yourself, these are the failure modes your engineering team has to fix at 3 AM. In a managed feed, these are our problem.

INCIDENTS PREVENTED · 12k+ monthly

AVG REPAIR TIME · · · < 4 hours

UPDATED · · · · · · 2026-05-19

01

Schema drift / DOM changes

92% of breaks · Silent data corruption if unmonitored

02

Anti-bot escalation

85% of breaks · Cloudflare/DataDome deploying new challenges

03

Target rate limiting

68% of breaks · IP bans and 429 Too Many Requests

04

Network timeouts

45% of breaks · Proxy pool exhaustion or target downtime

05

Data type coercion errors

30% of breaks · String prices breaking downstream SQL

// 06 — the data contract

Guaranteed schemas,

because broken data is worse than no data.

A managed data feed isn't just a cron job that runs a scraper. It's a strict data contract. At DataFlirt, every record is validated against a versioned schema before delivery. If a target site changes its layout and the price field goes missing, the pipeline halts the delivery of malformed records, alerts our on-call engineers, and quarantines the run. You never wake up to a database full of nulls.

Feed Delivery Status

Live telemetry for a managed B2B pricing feed.

feed.id b2b-pricing-eu

schedule daily · 00:00 UTC

schema.version v3.1

records.delivered 84,210

quarantined 0

freshness 42 seconds

sla.status compliant

Stay ahead of the pipeline

Data engineering
intel, weekly.

Anti-bot shifts, scraping infrastructure updates, dataset delivery patterns, and business outcomes from our pipelines. Short, technical, no fluff.

// 07 — FAQ

Common
questions.

About managed feeds, SLAs, data ownership, and how DataFlirt handles the chaos of the web so you don't have to.

Ask us directly →

What is the difference between a managed data feed and an API? +

An API is a pull mechanism; a feed is a push mechanism. APIs are designed for real-time, single-record lookups initiated by your application. Managed feeds are designed for bulk ingestion of entire datasets on a schedule (e.g., daily drops of 500k product listings into your data lake).

How do you handle target site redesigns? +

We monitor schema completeness in real-time. If a CSS selector breaks, our validation layer flags the missing fields and quarantines the records. Our on-call engineers patch the selector, bump the schema version if necessary, and backfill the data before your SLA window closes.

What formats and destinations do you support? +

We deliver JSON, JSON Lines (NDJSON), CSV, or Parquet. We can push directly to AWS S3, Google Cloud Storage, Azure Blob, Snowflake, or deliver via SFTP and webhook triggers. The format and destination are defined in your feed contract.

Who owns the data in a managed feed? +

You do. We act strictly as the extraction infrastructure. We do not resell your custom feed configurations or extracted datasets to your competitors, and we operate strictly within legal frameworks like the public data doctrine.

Can I get historical data or just ongoing feeds? +

Both. Most managed feed engagements start with a historical backfill — crawling the entire target to establish a baseline dataset — followed by delta (changes only) or full-refresh feeds on a daily, weekly, or monthly cadence.

How is pricing structured for managed feeds? +

Pricing is based on the complexity of the target (anti-bot difficulty), the frequency of delivery, and the volume of records. You pay a flat monthly fee for the SLA and the delivered data, not per-proxy or per-compute-hour. Predictable costs for predictable data.

$ dataflirt scope --new-project --target=managed-data-feed 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