ParAccel Course


ParAccel Course Overview

ParAccel accelerates analytics and helps companies accelerate, innovate, and compete. The ParAccel Analytic Platform combines an analytic database with advanced extensibility and integration technology to deliver big analytics anytime, anywhere. Fortune 1000 customers are testing the bounds of unconstrained analytics with the most prolific, most powerful, most expansive analytic platform.

Our analytic platform is a high-performance analytic database, designed from the ground up for speed. The database is surrounded with an extensibility framework analytic functions and supports on-demand integration of a variety of data and analytic results, right at the point of execution.

This allows ParAccel to leverage commodity hardware to perform extreme computing tasks. Columnar provides the efficiency required for BI queries to execute rapidly on spindle disks-based systems. Compression enhances the ability to store data and speeds up reads and writes. Simplicity rules it all. Simple to load, simple to query, simple to manage.

ParAccel is a software only columnar Big Data database that is both fast and simple. ParAccel is designed to handle complex BI tasks with extreme speed in a quickly changing business environment. A columnar database is a database that stores its values on disk one column at a time, as opposed to one row at a time.

Anyone who wanted to better their ETL skill sets by learning the happening tool in the Market. Knowledge in the database and/or data warehouse.

Build a graph adhering the business requirement. To blend different tools for different requirement and complete understanding of Data Warehousing and ETL terminologies. Knowledge about different components and its purpose

You will be hired as data analyst, ETL developer in the companies like Amazon, Apple, Waymo, google and more.

Communication fabric, optional storage area network (SAN), PADB features, performance, ParAccel Interconnect Protocol, Parallel Loading and Unloading and more.

ParAccel Course Syllabus


  • System Architecture
  • PADB Features
  • Columnar Orientation
  • Column vs. Row Example
  • How Does Columnar Orientation Impact Design Considerations?
  • Extensible Analytics
  • Query Compilation
  • Shared-Nothing Massively Parallel Processing (MPP)

ParAccel Interconnect Protocol

  • 9 Parallel Data Distribution, Query Planning and Execution
  • Incremental, Linear Scaling
  • Acceleration vs. Traditional DBMS Platforms Compression
  • Cost-Based Query Optimizer
  • Complex Join Processing
  • Query Concurrency
  • Highest Performance with Direct-Attached Storage
  • Using Memory to Boost Performance
  • High Performance in Optional SAN-Based Environments

Parallel Loading and Unloading

  • Standard Parallel Load
  • Massively Parallel Load
  • Parallel Extract
  • Mini-Batches and Stream Loads
  • Availability During a Disk Failure
  • Node Failover with a Hot Standby Node (HSN)
  • Compute Node Failover
  • Leader Node Failover
  • SAN-Based Node Failover with HSN
  • Disaster Recovery (D/R)
  • Snapshots (Snaps)
  • Load-and-Go Design.
  • Schema Neutral

The ParAccel Analytic Database

  • Hoc Query
  • Projections or Materialized Views
  • Standard Interfaces and Tools
  • SQL Coverage
  • Security Features
  • Appliance Simplicity on Standard Hardware
  • Platform Check