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    Connect to the Vertica Database With Astera Centerprise

    March 9th, 2023

    Vertica is a scalable analytics platform that can optimize both load and query performance. Vertica’s performance, high availability architecture, and parallel processing SQL query engine make it a preferred database for countless companies looking to scale up.

    Due to Vertica’s popularity, Astera Centerprise has recently introduced a built-in connector enabling easy, code-free access to the database. Once the connection is established, Vertica can be configured both as the source and destination objects to read and write data. Astera Centerprise also features pushdown capabilities, allowing businesses to transform the data after being loaded onto the Vertica database.

    What is Vertica Database?

    Vertica is a columnar data storage platform designed to manage huge volumes of data. This allows its users fast and efficient query performance along with providing high availability and scalability on enterprise servers. The prominent features of the Vertica database are:

    • Column-based storage organization
    • SQL interface with built-in analytics capabilities
    • Compression to cut storage costs
    • Compatible with programming interfaces
    • High performance and parallel data transfer

    Hassle-free Data Analysis

    Astera Centerprise’s code-free environment makes connecting to the Vertica database easy, quick, and hassle-free. Its out-of-the-box connectivity enables Vertica database integration with various file formats, databases, and REST APIs.

    Users can extract and load data from/to Vertica simply by configuring the database connection. Source data can also be cleaned, filtered, checked for integrity and inaccuracies, and modified in several other ways using the drag-and-drop transformations in Astera Centerprise.

    What Can Vertica Database Be Used For?

    Vertica offers features and capabilities for multiple use cases. Since businesses are dealing with data from several disparate sources, the Vertica database can be used to consolidate data, replicate entire databases, and even restore backups for quicker analysis.

    Vertica as a Source Object

    The following dataflow shows Vertica being used as a source to extract data and load it onto a PostgreSQL database.

    vertica database

    Figure 1: Dataflow showing data transfer from Vertica table to a PostgreSQL table

    The database table source object is dragged-and-dropped from the Toolbox to create this dataflow. Next, the database properties are configured, and the correct option is selected from the Data Provider drop-down list to connect to Vertica.

    connect to vertica database

    Figure 2: A Vertica database table being set up as a source object

    In this example, we will point the source object to the Customer Export table in the Properties page and select Full Load as the Read Strategy.

    vertica database table

    Figure 3: Selecting the table and the read strategy for the Customer Export table

    Next, a database table destination is dragged and dropped onto the designer window. This time, PostgreSQL is selected as the data provider.

    Configuring the Postgres destination table

    Figure 4: Properties of the PostgreSQL destination table

    A new table is created, and a data loading option is selected to write all the data onto the destination database table in a single batch.

    Selecting the load strategy for Postgres

    Figure 5: Selecting the load option for the Postgres destination table

     

    Using Vertica as a Destination Object

    Astera Centerprise can also be used to transform data from another source and load it to a Vertica database table. The following example illustrates configuring the Vertica database as a destination object.

    vertica database mapping

    Figure 6: Filter transformation being applied to data from a MySQL Customer table and loaded to the Vertica FilteredbyID table

    In this case, our source object is a MySQL table named Customer. A Filter transformation is applied to the data in the Customer table to filter the records with the required Store ID.

    The output of the Filter transformation is then mapped onto a Vertica database destination object.

    Configuring the Vertica destination table

    Figure 7: Properties of the Vertica destination table

    Vertica is selected as the Data Provider, and a new table named FilteredbyID is created. This is done to load all the data from the Filter transformation to a new table instead of existing ones.

    Creating a new Vertica database table

    Figure 8 Selecting the data load option for the FilteredbyID Vertica destination table

    How Does the Vertica Connector Help with Data Integration?

    The Vertica Connector for Astera Centerprise allows easy integration with numerous on-premise and online platforms and file formats. Centerprise can then process raw data using database lookups, aggregators, expressions, and more to extract value from data.

    Leverage Code-free Connection

    Using Vertica as a source or destination and leveraging its powerful analytical and storage capabilities is as simple as selecting the option from a drop-down list of supported platforms.

    Ensure Data Accuracy

    With Astera Centerprise, users can connect to the Vertica database and update trusted and accurate data as and when needed. Our data management platform features several data cleansing and validation transformations that can be used to maximize accuracy and relevance.

    Reduce Time-to-Insights

    Astera Centerprise’s automation capability removes multiple unnecessary steps, such as manually running dataflows and workflows every time the data is updated from the data integration process. Thus, it reduces time to insight and makes the entire process more efficient.

    Vertica is the database of choice for countless enterprises owing to its flexibility, scalability, and performance. With Centerprise’s Vertica connector, business users can quickly analyze big data from heterogeneous sources and make data-driven decisions to make their business grow.

    Authors:

    • Afnan Rehan
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