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WHITE PAPERS


LEANXCALE APPLICATIONs IN ADTECH

LeanXcale with its low latency and high performance key-value interface is able to handle in real-time very high data ingestion rates in the order of many millions of transactions per second with extreme levels of efficiency.

Its HTAP capabilities enable to perform real-time analytics over the operational data to maximize clicks and conversions.

LeanXcale scalable full ACID consistency guarantees that operational data is always consistent without creating bottlenecks.

The elasticity provided enables the reduction of cloud costs by minimizing the resources required to process the current workload.


Leanxcale Capabilities

  • LeanXcales Key-Value interface delivers the low latency and high performance required to process millions of transactions per second with extreme levels of efficiency.

  • HTAP capabilities provide the ability to perform any kinds of analytical queries over operational data to attain real-time analytics eliminating costly and complex data warehouse and ETL architectures.

  • Scalable full ACID consistency guarantees that data is always consistent.

  • LeanXcales Elasticity allows the dynamic adjustment of resources to match the incoming load to reduce operational expenses (power, cooling, 24x7 support, etc.).


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SUCCESFUL LEANXCALE USE CASES ON ADTECH

Tracking monthly more than 10 million profiles, Vikdata is the leading provider of small e-commerce second party data in Spain. Its data has been used in campaigns of banks like BBVA and Santander; BMW, WV, Volvo, Opel, Renault, and Skoda from the automotive sector; retailers like Carrefour or Lidl; insurance companies such as Mapfre and Santa Lucía Seguros, and many others like Bayer, Jamison or Mahou. LeanXcale is its preferred database helping in two critical aspects:

  • LeanXcale provides real-time analytics for the Vikdata platform main KPIs.

  • Vikdata's data scientific uses LeanXcale as an operational data lake, adding value to the data, by analyzing and making conclusions directly from the real-time data stream.