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MongoDB Media and Entertainment South Korea

Hankyoreh

Marketing Personalization

Hankyoreh website THE CHALLENGE Relational database bottlenecks Faced with new challenges and opportunities presented by digitalization, Hankyoreh made various efforts to adapt to the evolving media landscape.

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With an easy setup and a few clicks, MongoDB Atlas was deployed in a high availability (HA) three-node cluster configuration in 30 minutes with zero service interruption.

Reported impact

Business outcome

Personalized services made faster and more convenient with data

  • Customer Experience
  • Productivity Improvement
  • Speed to Market

Solution

Hankyoreh website THE CHALLENGE Relational database bottlenecks Faced with new challenges and opportunities presented by digitalization, Hankyoreh made various efforts to adapt to the evolving media landscape. A 400% increase in productivity with a flexible, fast platform Hankyoreh Talk to an Expert Korea’s Hankyoreh boosts productivity by 400% with MongoDB Atlas Industry Media Product MongoDB Atlas Use Case Content Management Customer since 2022 INTRODUCTION Hankyoreh, a leading voice today As publishing becomes increasingly digital, the media industry is continuously evolving. To this end, Hankyoreh is powering its digital journey with MongoDB Atlas, where it can manage everything from digital content to AI-curated news recommendation services on a single platform, creating a more engaging and richer experience for readers.

Data flow

Operational events and application data flow into MongoDB Atlas Search, where the platform stores current state and supports real-time queries for downstream applications and integrations such as Google Cloud.

Solution architecture

2 components · 2 layers
  1. Storage
    • MongoDB Atlas Stores the operational data and provides the managed document database foundation for Hankyoreh's workload.
  2. Serving
    • MongoDB Atlas Search Provides integrated full-text and faceted search across Hankyoreh's application data.

Architecture clues

  • APIs are a key integration layer in the application architecture.
  • Autoscaling is used to absorb demand spikes and control costs.
  • Full-text or faceted search runs inside the MongoDB platform.
  • High-availability cluster deployment is part of the design.
  • The deployment integrates with Google Cloud.

Evidence from the source

A 400% increase in productivity with a flexible, fast platform
Hankyoreh website THE CHALLENGE Relational database bottlenecks Faced with new challenges and opportunities presented by digitalization, Hankyoreh made various efforts to adapt to the evolving media landscape.
Personalized services made faster and more convenient with data
With an easy setup and a few clicks, MongoDB Atlas was deployed in a high availability (HA) three-node cluster configuration in 30 minutes with zero service interruption.
Transparency Evidence & methodology 86/100 reference value · 77% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value86/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity16/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact15/25
    1 metric describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence77%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    4 direct source quotes retained.
  • Date provenance0/10
    The publication date has no documented provenance.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity8/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. MongoDB

    Hankyoreh customer story

    First-party
    https://www.mongodb.com/solutions/customer-case-studies/hankyoreh
    Source type
    Vendor-published customer story
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes

Date evidence

  • First archived Aug 14, 2024 · Internet Archive · Independent First Wayback Machine capture; confirms the page existed by this date, not when it was published.
    Open date source
  • Sitemap last modified Jul 18, 2025 · MongoDB · Publisher metadata Publisher-reported modification timestamp; not a publication date.
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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