It's Time to Replace Spark

Xcalar - A Unified Platform for Analytics and AI

  • Next-Gen Data Engineering
  • SQL Analytics Across All Cloud Data
  • Data Apps with ML
  • Key Benefits

  • Use Spark SQL + Python
  • No multi-threaded programming needed
  • No Scala, RDDs, DataFrames, Executors, SDKs, etc.
  • Scale to 100s of nodes, 1000s of users, PBs of data
  • 10x cloud TCO savings over Spark
  • Transform gigabytes to petabytes of data with 5x developer productivity and 10x lower cloud TCO

    Xcalar Platform
    Scalability Copy@4x

    Scale to 100s of users, 1000s of nodes and petabytes of data

    Lower Cloud TCO Copy@4x

    10x cloud TCO savings over Apache Spark

    Developer Productivity Copy@4x

    5x developer productivity using Spark SQL + Python

    Our latest blog posts on data engineering and analytics

    Data Applications for Large Scale Data Transformations Made Easy – Three-part blog

    Part 1. Xcalar – The real “Spark“ behind Data Applications Introduction I want to start this three-part blog with a little introduction about Xcalar, and why I am excited to be here. Before joining Xcalar three years ago I spent most of my professional life building and managing Data and Analytics platforms at major Wall…

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    A Traffic Ticket Revenue Exercise in Xcalar: Part 2

    Xcalar is perfect for running large scale data transformations and enrichment to seamlessly combine and analyze data. Loading data into the Xcalar platform opens the door to easily working with large datasets in order to efficiently garner knowledge and insights. In this exercise, we work with NYC car ticket records from a few years as…

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    A Traffic Ticket Revenue Exercise in Xcalar: Part 1

    Xcalar is perfect for running large scale data transformations and enrichment to seamlessly combine and analyze data. Loading data into the Xcalar platform opens the door to easily working with large datasets in order to efficiently garner knowledge and insights. In this exercise, we work with NYC car ticket records from a few years as…

    Read More...

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