When Hadoop was introduced, it promised a faster time to insight because of simpler modeling using cheaper hardware.
But over time, organizations have been finding that Hadoop’s complexity and need for specialized skills are adding cost and headaches. Now instead of using their data for insight, many Hadoop shops are struggling with managing it.
With cloud services more mature, we’re seeing a lot of Hadoop customers migrating – or looking to migrate – to big cloud players like Google Cloud Platform, Amazon Web Services (AWS) and Microsoft Azure for data warehousing and analytics.
You may be wondering if this move is right for you.
To help you with your decision, we’ve put together a 30-minute webinar, hosted by Chris Presley, Pythian’s Director of Consulting and co-presented by Pythian Principal Consultant, Bjoern Rost, and Director of Engineering, Danil Zburivsky.
The presentation outlines Pythian’s experience with migrations from Hadoop to cloud and provides an outline of the things you need to consider when thinking about making the move to the cloud, including the cost benefits. These include:
The biggest benefit is the ability to decouple storage and compute, giving you pay-per-use savings on both sides. You can usually find cheaper storage in the cloud. And a careful look at your actual computing needs may reveal that daily or weekly reporting is plenty for most use cases, with round-the-clock computing needed for only a few.
With cloud, you don’t need to maintain permanent storage and can ramp up and down both storage and computing any time. This means you can save costs when you don’t need cloud services, then spend only as needed for storage or processing.
Cloud providers have made huge investments in data space, especially for data warehouses, giving you cost-for-performance ratios that small to mid-size business couldn’t achieve alone.
Save on in-house development by using third-party services for things like data management, cataloging, detailed auditing, complex queries and ML analysis.