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Handling Bursty Traffic in Real-Time Analytics Applications

Rockset

However, these databases tend to sacrifice support for complex SQL queries at any scale. Instead, these database makers have offloaded complex analytics onto application code and their developers, who have neither the skills nor the time to constantly update queries as data sets evolve.

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Data News — Week 23.12

Christophe Blefari

In small browser text areas you will be able to write Python, SQL or R code and orchestrate theses transformations with drag-n-drop. I'd have love to speak about tools offering to translate human langage to SQL like sequel.ai LinkedIn team decided to migrate to a lambda architecture and got 94% uplift in performance.

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An Overview of Real Time Data Warehousing on Cloudera

Cloudera

Optimized for point lookups, analytics, mutations, etc. Data streamed in is queryable in conjunction with historical data, avoiding need for Lambda Architecture. Figure 1 below shows a standard architecture for a Real-Time Data Warehouse. Analytics storage and query engine for pre-aggregated event data.