2006, Database-centric and Pipeline-centric

The Good and the Bad of Apache Spark Big Data Processing

AltexSoft

JULY 18, 2023

With its native support for in-memory distributed processing and fault tolerance, Spark empowers users to build complex, multi-stage data pipelines with relative ease and efficiency. On the other hand, this dependence on external storage systems can add an extra layer of complexity when integrating Spark into a data pipeline.

Big Data

Big Data Data Process Process Hadoop

Journey to Event Driven – Part 4: Four Pillars of Event Streaming Microservices

Confluent

MAY 9, 2019

Storing events in a stream and connecting streams via stream processors provide a generic, data-centric, distributed application runtime that you can use to build ETL, event streaming applications, applications for recording metrics and anything else that has a real-time data requirement. Out of the Tar Pit, 2006. Avro or Protobuf ).

Kafka

Kafka Pipeline-centric Architecture Database-centric

Data Engineering Digest

The Good and the Bad of Apache Spark Big Data Processing

Journey to Event Driven – Part 4: Four Pillars of Event Streaming Microservices

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