Columnar store is used in Vertica to improve the performance of sequential access by sacrificing the performance of single access. Compared with row-oriented databases which has to scan the whole table, only few needed columns are retrieved based on given queries in Vertica, which can improve throughput by reducing disk I/O costs.
Shared-nothing architecture is used in Vertica, where all nodes don't share anything in terms of memory and disk storage. Shared-nothing architecture are easier to scale, since there is no race or contention caused by locks. Moreover, Massively MPP(Massive Parallel Processing) architecture is used in Vertica, which can improve query performance such as increasing the throughput of large joins when multiple machines are involved.
Multi-version Concurrency Control (MVCC)
Vertica supports MVCC to achieve data consistency. Both current and previous statuses are stored and visible to transactions.
Decomposition Storage Model (Columnar)
Data is stored in Vertica in columnar format to improve query performance, since a lot of disk I/O can be avoided.
In Vertica, each node maintains checkpoints and transaction logs separately. The synchronization duration can be tuned by users as well. For a single-node failure, it can be recovered from other nodes. If the entire cluster fails, it can be recovered up to the earliest checkpoints when all nodes are good. New transaction log cannot be appended when a new checkpoint begins.
Delta Encoding Run-Length Encoding
Both Run-Length Encoding and Delta encoding are used in Vertica. RLE encoding is only used when the number of repetitions is large. Delta encoding works for INTEGER/DATE/TIME/TIMESTAMP/INTERVAL type, where the variations from the smallest value are stored instead of the real values to save more space.
https://www.vertica.com/docs/9.1.x/HTML/index.htm
MicroFocus
2005
HP, MicroFocus