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And yet when I see data engineering positions, particularly around here, it's all about Hadoop/HDFS, Spark, Cassandra, Mongo. I'm not saying there aren't use c
by SmellTheGlove 10y ago
And yet when I see data engineering positions, particularly around here, it's all about Hadoop/HDFS, Spark, Cassandra, Mongo. I'm not saying there aren't use cases for those, just that it seems like they've become the default basket of options rather than starting with an RDBMS and figuring out why you shouldn't use that.
I feel like a dinosaur working with Teradata all these years, but it hasn't failed me. Sure we spend some extra time modeling, and then some extra when we need changes, but other than the cost, it's really been solid.
- deleted 10y ago[deleted]
- threeseed 10y ago> but other than the cost Why do you think people are moving to Hadoop ? That cost that you glossed over is massive. Teradata is very, very expensive. It's great. It works. But it's expensive. Especially if you want to store large amounts of data e.g. networks or web traffic.
- SmellTheGlove 10y agoFair enough. I've been in large companies for too long, it seems. We'll pinch pennies over things like coffee and continuing education, but we're still paying those Teradata and SAS bills.