Cloud-Scale Platform For Analytics Applications

Develop & operationalize scale-out applications with simplicity, speed and scale

Snowflake + Xcalar❄️

Combining cloud-scale analytics with cloud warehousing

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Leverage existing technology, skills and open source libraries to analyze and manage your data with simplicity, speed, and scale


Open source machine learning libraries

Leverage TensorFlow, H2O, Scikit-learn and Keras to deploy machine learning workloads at cloud-scale - billions of classifications in seconds.

Leverage TensorFlow, H2O, Scikit-learn and Keras to deploy machine learning workloads at scale - millions to billions of classifications in seconds

Modern, open source development tools

Write reusable and manageable business logic with familiar languages like SQL, Python, and Jupyter Notebook.


Linear scalability

Extreme performance and scale: for your line-of-business business applications and your data pipeline workloads with 100s of nodes, 1000s of users, and petabytes of data.


Spark and Hadoop

Get 10x more productivity and operational efficiency out of your existing investments in Spark and Hadoop.

Why Xcalar

Build complex applications, handle huge workloads

Use visual programming, structured programming languages, and SQL to build complex business applications and handle your data transformation workloads including data preparation, data quality, and data governance within this single platform with simplicity, speed and scale with 10x savings in TCO.

Let your lake become your data warehouse

Break free from the limitations of traditional database silos to work directly off your data lake with a virtual data warehouse having the flexibility & scalability of the cloud.

Enterprise Grade

Connect to your existing databases, data warehouses, and Kafka platforms; Perform updates to tables at microbatch speeds while being ACID compliant; High operational performance can be obtained through redo logs, checkpoints and snapshots.

Xcalar Data Platform

Xcalar Design

A sophisticated IDE for creating cloud-scale applications

Xcalar Compute Engine

Scale-out, distributed, compute machinery to create the Xcalar runtime for user applications

Extract value directly from the data lake in near real-time


Data format agnostic

Use SQL, visual programming, and Python to work on virtual tables derived instantly from structured, semi-structured and unstructured data.


BI tools query real-time data

Let your BI tools access live cubes and virtual tables that can be transactionally updated in real-time with insert/modify/delete microbatches, bypassing long running batch jobs.


Eliminate copying & movement of data

Xcalar’s True Data in Place™ technology does not require data to be moved or copied allowing you to work directly off the data lake.

Do your develop > test > operationalize cycles take too long?

Xcalar Design provides a powerful paradigm for business logic using SQL, Python code and visual programming with point-and-click simplicity to develop, test and deploy your analytics applications and ML workloads to production at petabyte scale, resulting in the fastest develop > test > operationalize cycle in the industry.

Hiring skilled personnel for big data is becoming increasingly harder. Would you rather leverage the more commonly available skills like SQL, Python and visual programming than consider re-training your workforce?

With Xcalar, you can increase DBA, business analyst and developer productivity by over 10x.

Do you have to deploy multiple clusters to simultaneously accommodate different types of workloads — such as batch jobs, latency-sensitive jobs, and ad hoc analytics?

Xcalar’s mixed mode feature solves this problem.

Your data is growing exponentially. Do you find that it takes increasingly longer to derive business intelligence? Do your dashboards show data that is hours or a day old?

With Xcalar’s True Data in Place™ technology you can gain real-time business insights.

Are you limited by your hardware-centric traditional database silo? Do you need the scale and elasticity of the cloud?

With Xcalar you can migrate to a virtual data warehouse at cloud-scale.

As your data storage needs to grow and your compute becomes more complex, do you over or under provision for cloud resources? Are your cloud bills soaring? Are you wasting money on idling CPU, memory or disk?

Xcalar addresses this problem by allowing separate scaling of storage and compute.

With ever increasing data sources, growing transformation complexity, and the need to incorporate ML at every step, is auditing, tracing lineage and understanding the details of your pipeline becoming more difficult?

For every step of your dataflow, Xcalar provides a detailed visual representation of all data sources, operations performed, lineage, data skew, and any schema changes made.

Deploy in your preferred environment


Private cloud


Public cloud



Key Use Cases

Developing and operationalizing complex business logic and ML algorithms at cloud-scale

Interactively work with petabytes of data; billions of classifications in seconds

Virtual data warehousing and ad hoc analytics

Migrate your traditional DWs to an open scale-out architecture

Data transformation and quality at petabyte scale

Work with trillion rows; process petabyte scale batch data in seconds or minutes

Live data for BI and reporting

Unlock your data lake for your analysts and data scientists

Check out our latest events and blogs

Xcalar accelerates time-to-value in various industries


Xcalar reduced overall time-to-value from 24 hours to 27 seconds

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Xcalar provided significant resource cost savings by decoupling compute from storage

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Ad Tech

Xcalar provided 10x cost savings over the existing Hadoop/Hive approach

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Xcalar improved developer productivity by 10x

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