It's the same with any new shiny technology it seems.
The specific thing I have experience with is in analytics/relational databases. Suddenly around 8-10 years ago it became imperative for every client I was dealing with to migrate their RDBMSes to Hadoop/Hive setups, even when their largest dataset was only about 120M rows denormalized.
They were trading three servers (primary, backup, DR) for sometimes 15 to 20. Queries that MSSQL was handling sub-second were suddenly taking 45s on Hive. It was utter madness and was as far as I can tell driven by good salespeople, FOMO, and the feeling of importance of being able to say your company is running Big Data(TM?).
I saw maybe one implementation (of dozens) that actually stayed in use for any length of time.
The specific thing I have experience with is in analytics/relational databases. Suddenly around 8-10 years ago it became imperative for every client I was dealing with to migrate their RDBMSes to Hadoop/Hive setups, even when their largest dataset was only about 120M rows denormalized.
They were trading three servers (primary, backup, DR) for sometimes 15 to 20. Queries that MSSQL was handling sub-second were suddenly taking 45s on Hive. It was utter madness and was as far as I can tell driven by good salespeople, FOMO, and the feeling of importance of being able to say your company is running Big Data(TM?).
I saw maybe one implementation (of dozens) that actually stayed in use for any length of time.