Data Virtualization

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Xcalar Data Platform and Xcalar VDW are architected based on core data virtualization concepts, and resulted in our data virtualization technology, True Data In Place™.

Data silos make data access difficult and slow down the analytics process. Common practices are to copy data to the data lake or federate queries to source databases. The techniques come with some limitations, for example copying is slow and risks synchronization issues, and query federation adds significant load to underlying databases and impacts their SLAs.

Using True Data In Place™, Xcalar Data Platform and Xcalar VDW work with diverse data sources in their original locations, leveraging metadata to optimize data processing performance on petabyte-scale data and to minimize network use. Unlike other virtualization solutions, Xcalar Data Platform and Xcalar VDW provide advanced data modeling and transformation capabilities, including visual modeling tools to empower non-IT users to combine data from different sources and accelerate the analytics process.

True Data in Place

Xcalar products work directly with source data files without copying data into an internal format.


Xcalar products support all major cloud and on-prem storage, including Microsoft Azure Storage, Amazon S3, Google Cloud Storage, HDFS, and Kafka, as source or export locations.

Separation of storage from compute

Xcalar products meet processing and storage needs for sustained and burst workloads by scaling compute and storage independently.

Data format-agnostic

Xcalar products work with structured, semi-structured, or unstructured source data of any format.

Fast access to streaming data

Xcalar products provide connectors to or from real-time and streaming data sources for low-latency or high-throughput processing of data.

Lineage and auditability

Dataflows provide an auditable way to provide detailed information about schemas, distribution of data across nodes, hash coloration, and data skew.

JDBC and REST access

Many users concurrently access data via optimized JDBC queries using BI applications, such as Tableau, Qlik, and Power BI.


Xcalar products’ scale-out compute architecture provides the highest level of performance achievable for both read and write operations, and it provides near-linear scalability across thousands of servers.

Full memory hierarchy

Xcalar products use more than just server memory; they prioritize use of the entire memory hierarchy–DRAM, SSD, and disk.  Active data is automatically prioritized and stored in memory, while inactive data is pushed to SSD and disk.

Administration and system management

Administrators tune Xcalar clusters using dashboards that describe resource utilization, workload operationalization, and data skew within a cluster.

Security and authentication

Xcalar products support integration with Kerberos, LDAP, OAUTH, and custom authentication services for authentication and user management.


Data Engineer

Related Product Offering

Use Cases

10X performance improvement by decoupling compute from storage

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Time to value reduced from 3 months to 4 days               

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3X increase in analyst productivity

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Analyzing new data from 24 hours to 27 seconds

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Data Prep and Quality

Refine your data and accelerate your analytics cycle.

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Data Warehousing

Meet your SLAs when processing micro-batch updates.

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Live Data for BI and Reporting

Unlock your data lake for analysts and data scientists.

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Data Virtualization

Access all your data without data movement.

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