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About VMware Greenplum

VMware Greenplum is a data analytics platform from VMware that supports the rapid creation and deployment of models for complex applications. It combines advanced analytics, machine learning capabilities, and data orchestration to help organizations use their data effectively. VMware Greenplum is designed for enterprise-level analytics, providing a reliable environment for processing large volumes of data. This platform enables teams to conduct data analysis using SQL and integrates smoothly with various data science tools. Key capabilities: advanced analytics machine learning data orchestration SQL support large-scale data processing Best for: data scientists and analysts that need to build and deploy analytics models at scale.

VMware Greenplum Details

Vendor
VMware
Year Launched
1989
Location
3401 Hillview Ave, Palo Alto, CA, United States, California
Deployment
cloud
Training Options
demo, account manager, community
Countries Served
All Countries
Languages
English, Spanish, French, German, Italian, Japanese, Korean, Portuguese, Russian, Chinese
Users
businesses of all sizes
Industries Served
Healthcare, Education, Finance, Retail, Manufacturing, Technology
Tags
Cloud Infrastructure, Virtualization, Cloud Management, Software-Defined Data Center, Network Virtualization, vSAN, Hybrid Cloud, Public Cloud, Private Cloud, Desktop Virtualization, Multi-Cloud, SDDC, IT Operations, Mobility, Security, Open Source, Cloud Services, Cloud Security, Data Center Security, Digital Workspace, Digital Transformation, Security, Storage, Hyper-Converged Infrastructure, Big Data, Application Security, Data Center Automation, Data Center Operations, Cloud-Native Applications, and Open Source

VMware Greenplum's In-App Market Place

Does VMware Greenplum have an in-app market place?

Yes

How many Mini-Apps in the marketplace?

0

Mini Apps

Pricing Options

Free trial
Free version
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Accepted Payment Currencies

USD ($), EUR (€), GBP (£), JPY (¥), AUD (A$), CAD (C$), CHF (CHF), CNY (¥), SEK (kr), NZD (NZ$), KRW (₩), INR (₹), SGD (S$), HKD (HK$), RUB (₽), NOK (kr), MXN (Mex$), ZAR (R), BRL (R$).

Pros & Cons

  • 1. Excellent scalability for large data workloads.
  • 2. High query performance for complex scenarios.
  • 3. Broad compatibility with PostgreSQL and Oracle systems.
  • 4. Built-in geospatial and AI analytics tools.
  • 5. Robust support for big data and cloud deployments.
  • 1. Steeper learning curve for users unfamiliar with MPP systems.
  • 2. Requires significant computational resources.
  • 3. Limited user interface for beginners.
  • 4. Relies heavily on expert optimization for best performance

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