ElephantDB: a distributed database specialized in exporting data from Hadoop(tech.backtype.com) |
ElephantDB: a distributed database specialized in exporting data from Hadoop(tech.backtype.com) |
The answer is simplicity and robustness. HBase is a very complex system. It's a monster to configure and operate. If you don't need random write capabilities and a K/V data model is sufficient for you, HBase may be overkill.
ElephantDB has very little moving parts, so it "just works." Additionally, if you make an update and write bad data to ElephantDB, you can easily delete the bad version and roll back to a version with good data.
At the end of the day, they target different use cases.
To be fair, HBase has this too. As long as you don't overwrite 3 times (configurable, on a per-column family basis), you are fine.
I must say that an alternative to HBase which just works is mighty tempting. I'm using HBase, and about half of the nasty problems I've run into have been caused by either HBase directly or making HBase talk to Django (the thrift interface works nicely in batch jobs, but causes all sorts of problems in a webapp). Will definitely check out elephant.
The ElephantDB versions are totally independent from one another, whereas with HBase they're stored in the same index. The only tradeoff to storing more ElephantDB versions is using more space on the distributed filesystem. ElephantDB versions don't go away until you delete them, which lets you use whatever strategy you want to manage versions. For example, you may decide to keep one version each month, and every version for the past week. This lets you do analytics that looks at your data from long ago.