DBDB.io The Encyclopedia of Database Systems · Est. 2017
Database of Databases

Database Entry

Vertica


Vertica is a distributed infrastructure-independent analytics platform. It can be deployed on various platforms like AWS,GCP,Azure...[02]

Country of Origin
US
Start Year
2005 [02]
Project Type
Commercial
Written in
C++
Supported Languages
C++, Java, Perl, Python, R
Derived From
PostgreSQL
Inspired By
C-Store
Operating System
Linux
License
Proprietary

It is designed to support a relatively high query performance compared with traditional DBMS. High availability and good scalability on commodity hardware can be achieved. Also, it supports good integration with Hadoop, which makes user choose where they want to analyze data.

Database Entry

Vertica


Vertica is a distributed infrastructure-independent analytics platform. It can be deployed on various platforms like AWS,GCP,Azure... It is designed to support a relatively high query performance compared with traditional DBMS. High availability and good scalability on commodity hardware can be achieved. Also, it supports good integration with Hadoop, which makes user choose where they want to analyze data.[02]

History[02]


Vetica was founded by Michael Stonebraker and Andrew Palmer in 2015. Vertica is derived from C-Store. C-Store is a prototype developed by MIT and few other universities like Brown. It was acquired by Hewlett Packard in 2011.Moreover, it also joined Micro Focus in 2017 due to the merger between Micro Focus and HP.

Checkpoints[03][04]


In Vertica, each node maintains checkpoints and transaction logs separately. The synchronization duration can be tuned by users. For a single-node failure, it is recovered from other nodes. If all nodes face failures, the database is recovered to the earliest checkpoints where all nodes are good. No new transaction log will be appended, if a new checkpoint starts in Vertica.

Concurrency Control[05][06]


Vertica supports Multi-version Concurrency Control for data consistency. Apart from current status, previous status are also visible to transactions, Transaction isolations can be achieved here since there is no conflict between the read and write operations. A shared-nothing parallel processing architecture has been adopted in Vertica, which can prevent the overhead from locks.

Data Model[07]


Columnar store is used in Vertica to improve the performance of sequential record access, even if the performance of single record have to be degraded. Compared with row-oriented databases which scan the whole table, only few columns are retrieved for given query, which can improve throughput by reducing I/O operations.

Query Interface


SQL

Storage Architecture


Storage Model


System Architecture


Citations

7 sources
  1. http://www.vertica.com vertica.com Spam — Check Archive
  2. Vertica - Wikipedia wikipedia.org
  3. Troubleshooting Tips for the Vertica Catalog vertica.com Dead — Check Archive
  4. https://blogs.opentext.com opentext.com Dead — Check Archive
  5. https://db-engines.com/en/system/MemSQL;Vertica db-engines.com
  6. https://www.vertica.com/blog/concurrency-workload-management vertica.com
  7. Advanced Analytics for Data Warehouse & Data Lakehouse vertica.com Dead — Check Archive
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