"Data is new oil of 21st century"
"By 2025, it is estimated that there will be more than to 21 billion IoT devices"
"41.5 billion IoT devices will be generating 79.4 zettabytes of data in 2025"
In a global view, we think that data architecture, and more widely big data architecture, cannot be shorted as “Hadoop or not” solution. Each need, each business case from our customers must be identified and must be analyzed to find the best solution.
In the beginning (2000-2010), some customers decide to migrate their data platforms on Hadoop (bare metal) platforms to reduce their dependencies to high costs licenses from DBs, tools editors, etc.
ROI was the first reason to migrate all data from classical databases to Hadoop. Some of them discover, after all, some pain points:
- Hadoop cannot answer to all their needs, especially on visualization side because of connectors,
- In his initial form (2000-2010), Hadoop is more batch/micro-batch processing tool for large dataset rather than real-time processing tool,
- Database in Hadoop (Hive) ecosystem is slow compared to traditional databases,
- Maintenance is painful because customers deal with infrastructure, OS and Software layers issues/migrations