Frankly, I would look at the eco-system around HBase, and HDFS in general. You have at least four different SQL solutions on HBase. You have a number of Graph solutions on HBase. Hive, Spark, ... and a number of technologies / solutions supporting HDFS, support HBase as well. The HDFS eco-system supports other data structures / models as well, such as column stores, etc. Is eventually consistent important to you? Is HBase the only HDFS centric technology you will use, where other components of the distros look like "overhead" to you compared to Cassandra? Ultimately, what is your strategic architecture to support varied workloads and data models on the same platform. If you can answer that question, then the choices should become easier. As others have said you would get a pretty biased opinion from this group since we have all committed to HBase for one reason or the other. We committed to it also because of the extensive eco-system and enterprise capabilities that are being built into that eco-system, such as manageability, security, governance, etc. by the distro vendors. Things we can leverage to provide a full-fledged platform for Big Data to enterprises, and not just a Big Table implementation. Not sure how integrated Cassandra is into that entire eco-system.
Rohit -----Original Message----- From: Neelesh [mailto:[email protected]] Sent: Wednesday, November 30, 2016 10:08 AM To: [email protected] Subject: Re: Hbase on HDFS versus Cassandra We use both, in different capacities. Cassandra is an x-DC archive store with mostly batch writes and occasional key based reads. Hbase is for real-time event ingestion. Our experience so far on hbase + phoenix is that when it works, it is fast and scales like crazy. But if you ever hit a snag around data patterns, you will have a VERY hard time figuring out what's going on. A combination of global phoenix indexes and heavy writes leave an entire cluster sluggish, if there is a hint of hotspotting. On the other hand, we had a big struggle getting Cassandra when a node recovery was in progress. What with twice the amount of disk requirements during recovery etc. Other than that, it is quiet. But the access patterns are not the same. I think the old rule still stays. If you are already on hadoop , or interested in using/analysing data in several different ways, go with hbase . If you just need a big data store with a few predefined query patterns, Cassandra is good Of course, I'm biased towards HBase. On Nov 30, 2016 7:02 AM, "Mich Talebzadeh" <[email protected]> wrote: > Hi Guys, > > Used Hbase on HDFS reasonably well. Happy to to stick with it and more with > Hive/Phoenix views and Phoenix indexes where I can. > > I have a bunch of users now vocal about the use case for Cassandra and > whether it can do a better job than Hbase. > > Unfortunately I am no expert on Cassandra. However, some use case fit would > be very valuable. > > Thanks > > Dr Mich Talebzadeh > > > > LinkedIn * https://www.linkedin.com/profile/view?id= > AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw > <https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCd > OABUrV8Pw>* > > > > http://talebzadehmich.wordpress.com > > > *Disclaimer:* Use it at your own risk. Any and all responsibility for any > loss, damage or destruction of data or any other property which may arise > from relying on this email's technical content is explicitly disclaimed. > The author will in no case be liable for any monetary damages arising from > such loss, damage or destruction. >
