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Features of HP Vertica

  • Difficulty Level : Hard
  • Last Updated : 04 Nov, 2019

Below are the features of HP Vertica and why you should use it apart form the traditional databases management systems. HP Vertica is database product that is used for handling huge amounts of data or big data. It is relational database management system that is built for analytics purpose.

Features of HP Vertica:
These are following as below:

  1. Columnar orientation:
    In HP vertica the data is stored in the form of columns rather than in the row wise storage. The main reason for the columnar storage of the data is to minimize the read and write operation’s and also to retrieve the query output faster.
  2. Advanced Compression:
    Encoding and the compression techniques are used to optimize the query performance and save the storage space. Query performance and save storage space. Encoding is the process of converting data into a standard format. Encoded data can be processed directly by Vertica.

    Compression is the process of transforming data into a compact format. Compressed data cannot be directly processed by Vertica. Data must first be decompressed. Most commonly used encoding and compression methods are Run-Length Encoding(RLE), Deltaval encoding and LZO(Lempel-Ziv-Oberhumer-based) compression.



  3. High Availability:
    Vertica is designed for high availability. High availability is the ability of the database to continue running even if a node goes down. If a node fails, a copy is available on one of the surviving nodes as shown below.

    Vertica automatically recovers missing data by querying other nodes.

  4. Massive Parallel Processing:
    Vertica is a shared nothing architecture, it allows each node in the cluster to work on its portion of database when running a query.

    Public network is used for communication with outside world.Private network is used for intra node communication(query plans, query results, data loads).

    We can load data continuously in real time to any node. The request will be equally distributed and managed by making one of the node initiator of query execution and others as executors.

  5. Application Integration:
    HP vertica combines the data form different locations or different data sources which is known as application integration. The ETL(Extraction , Transform and load ) tools are used to pull the data form different databases and convert them to a standard form and place it into another databases repository.
  6. Automatic Databases Design:
    To efficiently design the databases automatically, HP vertica uses a tool known as the database designer. When data is loaded into vertica from a row-store data source, vertica transforms the data into column-based projections.

    Projections are not formed on the creation of the tables but they are formed on the initial load of the data into the database table.

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