Comparing Vertica, ParAccel and Exasol

I talked with executives at Nuremberg, Germany-based Exasol last week - at 5:00 am ET! - and of course want to blog about it. For clarity, I'd like to start by comparing/contrasting the fundamental data structures at Vertica, ParAccel, and Exasol. And it feels like that should be a separate post. So here goes.• Exasol, Vertica, and ParAccel all store data in columnar formats.

• Exasol, Vertica, and ParAccel all compress data heavily.

• Exasol, Vertica, and ParAccel all - perhaps to varying extents - operate on in-memory data in compressed formats.

• ParAccel and Exasol write data to what amounts to the in-memory part of their basic data structures; the data then gets persisted to disk. Vertica, however, has a separate in-memory data structure to accept data and write it to disk.

• Vertica is a disk-centric system that doesn't rely on there being a lot of RAM.

• ParAccel can be described that way too; however, in some cases (including on the TPC-H benchmarks), ParAccel recommends loading all your data into RAM for maximum performance.

• Exasol is totally optimized for the assumption that queries will be run against data that had already been previously loaded into RAM.

Beyond the above, I discuss in this separate post how Exasol does MPP shared-nothing, software-only columnar data warehouse database management differently than Vertica and ParAccel.I talked with executives at Nuremberg, Germany-based Exasol last week - at 5:00 am ET! - and of course want to blog about it. For clarity, I'd like to start by comparing/contrasting the fundamental data structures at Vertica, ParAccel, and Exasol. And it feels like that should be a separate post. So here goes.