August 22, 2017

Imanis Data

I talked recently with the folks at Imanis Data. For starters:


Imanis correctly observes that there are multiple reasons you might want to recover from backup, including:

Imanis uses the phrase “point-in-time backup” to emphasize its flexibility in letting you choose your favorite time-version of your rolling backup.

Imanis also correctly draws the inference that the right backup strategy is some version of:

Note: When Imanis backups offer direct query access, the possibility will of course exist to use the backup data for general query processing. But while that kind of capability sounds great in theory, I’m not aware of it being a big deal (on technology stacks that already offer it) in practice.

The most technically notable other use cases Imanis mentioned are probably:

Imanis views its competition as:

Beyond those, the obvious comparison to Imanis is Delphix. I haven’t spoken with Delphix for a few years, but I believe that key differences between Delphix and Imanis start:

Imanis software runs on its own cluster, based on hacked Hadoop. A lot of the hacking seems to relate to a metadata store, which supports things like:

Another piece of Imanis tech is machine-learning-based anomaly detection.

The technology for this seems rather basic:

But in general concept this is something a lot more systems should be doing.

Most of the rest of Imanis’ tech story is straightforward — support various alternatives for computing platforms, offer the usual security choices, etc. One exception that was new to me was the use of erasure codes, which seem to be a generalization of the concept of parity bits. Allegedly, when used in a storage context these have the near-magical property of offering 4X replication safety with only a 1.5X expansion of data volume. I won’t claim to have understood the subject well enough to see how that could make sense, or what tradeoffs it would entail.


One Response to “Imanis Data”

  1. J-Luc Billy on August 23rd, 2017 5:04 am

    Erasure coding will be a new Hadoop 3 feature, cf. for the motivation (as of 2015) and for the results (as of 2016)

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