Rockset

MAY 12, 2022

Databases could just buffer, ingest and query data on a regular schedule. Moreover, analytical systems and pipelines were complementary, not mission-critical. Analytics wasn’t embedded into applications or used for day-to-day operations as it is today. Offloading complex analytics onto data applications.

Analytics Application 52

Analytics Application Lambda Architecture Hadoop Electronics 52

Christophe Blefari

MARCH 24, 2023

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.

Lambda Architecture 130

Lambda Architecture Data Pipeline Data SQL 130

Cloudera

NOVEMBER 2, 2020

Data processing and analytics drive their entire business. So they needed a data warehouse that could keep up with the scale of modern big data systems , but provide the semantics and query performance of a traditional relational database. Optimized for point lookups, analytics, mutations, etc. Data Model. Tech Preview).

Data Warehouse 97

Data Warehouse Kafka Lambda Architecture Telecommunication 97