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support

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Description

IBM Analytics Engine offers a unique architecture for Hadoop clusters by separating the compute and storage components. Rather than relying on a fixed cluster with nodes that serve both purposes, this engine enables users to utilize an object storage layer, such as IBM Cloud Object Storage, and to dynamically create computing clusters as needed. This decoupling enhances the flexibility, scalability, and ease of maintenance of big data analytics platforms. Built on a stack that complies with ODPi and equipped with cutting-edge data science tools, it integrates seamlessly with the larger Apache Hadoop and Apache Spark ecosystems. Users can define clusters tailored to their specific application needs, selecting the suitable software package, version, and cluster size. They have the option to utilize the clusters for as long as necessary and terminate them immediately after job completion. Additionally, users can configure these clusters with third-party analytics libraries and packages, and leverage IBM Cloud services, including machine learning, to deploy their workloads effectively. This approach allows for a more responsive and efficient handling of data processing tasks.

Description

Accelerate your journey to a fully operational Kubernetes setup and streamline lifecycle management with Nutanix Kubernetes Engine, an advanced enterprise solution for managing Kubernetes. NKE allows you to efficiently deliver and oversee a complete, production-ready Kubernetes ecosystem with effortless, push-button functionality while maintaining a user-friendly experience. You can quickly deploy and set up production-grade Kubernetes clusters within minutes rather than the usual days or weeks. With NKE’s intuitive workflow, your Kubernetes clusters are automatically configured for high availability, simplifying the management process. Each NKE Kubernetes cluster comes equipped with a comprehensive Nutanix CSI driver that seamlessly integrates with both Block Storage and File Storage, providing reliable persistent storage for your containerized applications. Adding Kubernetes worker nodes is as easy as a single click, and when your cluster requires more physical resources, the process of expanding it remains equally straightforward. This streamlined approach not only enhances operational efficiency but also significantly reduces the complexity traditionally associated with Kubernetes management.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Acquia CDP Yes 
Apache Spark Yes 
Galileo Yes 
Hadoop Yes 
IBM Cloud Object Storage Yes 
Kubernetes No 
MINT Yes 
Nutanix Kubernetes Platform No 
RadiantOne Yes 
Switch Automation Yes 
ZARUS Yes 
groundcover No 

Integrations

Acquia CDP No 
Apache Spark No 
Galileo No 
Hadoop No 
IBM Cloud Object Storage No 
Kubernetes Yes 
MINT No 
Nutanix Kubernetes Platform Yes 
RadiantOne No 
Switch Automation No 
ZARUS No 
groundcover Yes 

Pricing Details

$0.014 per hour
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person No 

Vendor Details

Company Name

IBM

Founded

1911

Country

United States

Website

www.ibm.com/cloud/analytics-engine

Vendor Details

Company Name

Nutanix

Founded

2009

Country

United States

Website

www.nutanix.com/products/kubernetes-engine

Product Features

Data Discovery

Contextual Search No 
Data Classification No 
Data Matching No 
False Positives Reduction No 
Self Service Data Preparation No 
Sensitive Data Identification No 
Visual Analytics No 

Data Visualization

Analytics No 
Content Management No 
Dashboard Creation No 
Filtered Views No 
OLAP No 
Relational Display No 
Simulation Models No 
Visual Discovery No 

Product Features

Container Management

Access Control No 
Application Development No 
Automatic Scaling No 
Build Automation No 
Container Health Management No 
Container Storage No 
Deployment Automation No 
File Isolation No 
Hybrid Deployments No 
Network Isolation No 
Orchestration No 
Shared File Systems No 
Version Control No 
Virtualization No 

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