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What is Rocket Data Virtualization?

Traditional methods for integrating mainframe data, like ETL, data warehouses, and connector development, are becoming increasingly insufficient in terms of speed, accuracy, and efficiency in the current business environment. With the ever-growing volume of data generated and stored on mainframes, these timeworn approaches are increasingly outpaced. Data virtualization presents itself as a modern solution to this widening gap, streamlining the access of mainframe data for both developers and applications. This innovative method enables organizations to identify and map their data just once, allowing for easy virtualization and reuse across multiple platforms. Consequently, this capability ensures that data remains in alignment with overarching business objectives and goals. By implementing data virtualization on z/OS, organizations can effectively navigate the complexities associated with mainframe resources. Furthermore, data virtualization promotes the integration of information from various disparate sources into a unified logical repository, which significantly enhances the connection between mainframe data and distributed applications. In addition, this technique allows for the enrichment of mainframe data through the incorporation of insights derived from location, social media, and other external datasets, leading to a more holistic understanding of business dynamics. As organizations seek to remain competitive, embracing such advanced methodologies can foster agility and innovation in decision-making processes.

What is Dremio?

Dremio offers rapid query capabilities along with a self-service semantic layer that interacts directly with your data lake storage, eliminating the need to transfer data into exclusive data warehouses, and avoiding the use of cubes, aggregation tables, or extracts. This empowers data architects with both flexibility and control while providing data consumers with a self-service experience. By leveraging technologies such as Apache Arrow, Data Reflections, Columnar Cloud Cache (C3), and Predictive Pipelining, Dremio simplifies the process of querying data stored in your lake. An abstraction layer facilitates the application of security and business context by IT, enabling analysts and data scientists to access and explore data freely, thus allowing for the creation of new virtual datasets. Additionally, Dremio's semantic layer acts as an integrated, searchable catalog that indexes all metadata, making it easier for business users to interpret their data effectively. This semantic layer comprises virtual datasets and spaces that are both indexed and searchable, ensuring a seamless experience for users looking to derive insights from their data. Overall, Dremio not only streamlines data access but also enhances collaboration among various stakeholders within an organization.

Media

Media

Integrations Supported

Apache Iceberg
Apache Superset
Azure Marketplace
Cyral
DashboardFox
DataClarity Unlimited Analytics
Emgage
HPE Ezmeral
Hex
IBM Cloud
Looker
Okera
Preset
Privacera
Protegrity
PuppyGraph
SQL
Yurbi
data.world
witboost

Integrations Supported

Apache Iceberg
Apache Superset
Azure Marketplace
Cyral
DashboardFox
DataClarity Unlimited Analytics
Emgage
HPE Ezmeral
Hex
IBM Cloud
Looker
Okera
Preset
Privacera
Protegrity
PuppyGraph
SQL
Yurbi
data.world
witboost

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Rocket

Date Founded

1990

Company Location

United States

Company Website

www.rocketsoftware.com/product-categories/data-virtualization

Company Facts

Organization Name

Dremio

Date Founded

2015

Company Location

United States

Company Website

www.dremio.com

Categories and Features

Categories and Features

Big Data

Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates

Data Lineage

Database Change Impact Analysis
Filter Lineage Links
Implicit Connection Discovery
Lineage Object Filtering
Object Lineage Tracing
Point-in-Time Visibility
User/Client/Target Connection Visibility
Visual & Text Lineage View

Data Warehouse

Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge

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