Data Ingestion Vs. Cluster Migration: Top Differences

Here are the differences between Data ingestion and Cluster migration. Data ingestion and cluster migration are two distinct processes used in data management.

Data Ingestion

Data ingestion

Data ingestion involves the process of taking in data from various sources, such as databases, file systems, and streaming platforms, and making it available for processing and analysis.

This can involve cleansing, transforming, and formatting the data so that it can be used in analytics applications.

Examples of data ingestion tools include Apache Kafka, Amazon Kinesis, and Google Pub/Sub.

Cluster Migration

Cluster migration

Cluster migration, on the other hand, involves moving an entire cluster of computing resources from one environment to another.

This can include moving from on-premise to cloud-based infrastructure, or from one cloud provider to another.

The goal of cluster migration is to improve scalability, reliability, and cost-efficiency.

Examples of cluster migration tools include AWS Database Migration Service, Google Cloud Data Transfer, and Azure Database Migration Service.


Author: Srini

Experienced software developer. Skills in Development, Coding, Testing and Debugging. Good Data analytic skills (Data Warehousing and BI). Also skills in Mainframe.