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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.
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