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Average Ratings 0 Ratings

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ease
features
design
support

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Description

NetApp MetroCluster setups consist of two geographically distinct, mirrored ONTAP clusters that function together to ensure ongoing data availability and SVM safeguarding. Each cluster continuously replicates its data aggregates to its counterpart, ensuring that both locations maintain identical copies of the data. In case one of the sites experiences a failure, administrators can quickly activate the mirrored SVM on the operational cluster, allowing for uninterrupted data service. The MetroCluster system accommodates both fabric-attached (FC) and IP-based cluster configurations: the fabric-attached MetroCluster utilizes FC transport for SyncMirror synchronization between sites, while MetroCluster IP operates over layer-2 stretched IP networks. Deployments of Stretch MetroCluster facilitate coverage across an entire campus, and with ONTAP versions 9.12.1 and 9.15.1, MetroCluster IP configurations can support up to four nodes using NVMe/FC or NVMe/TCP. Furthermore, it is important to note that front-end SAN protocols such as FC, FCoE, and iSCSI are fully supported within this architecture, enhancing the overall versatility of MetroCluster solutions. This flexible design accommodates various enterprise needs, making it an attractive option for organizations looking to optimize their data management strategies.

Description

Oracle Big Data Service simplifies the deployment of Hadoop clusters for customers, offering a range of VM configurations from 1 OCPU up to dedicated bare metal setups. Users can select between high-performance NVMe storage or more budget-friendly block storage options, and have the flexibility to adjust the size of their clusters as needed. They can swiftly establish Hadoop-based data lakes that either complement or enhance existing data warehouses, ensuring that all data is both easily accessible and efficiently managed. Additionally, the platform allows for querying, visualizing, and transforming data, enabling data scientists to develop machine learning models through an integrated notebook that supports R, Python, and SQL. Furthermore, this service provides the capability to transition customer-managed Hadoop clusters into a fully-managed cloud solution, which lowers management expenses and optimizes resource use, ultimately streamlining operations for organizations of all sizes. By doing so, businesses can focus more on deriving insights from their data rather than on the complexities of cluster management.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Hadoop No 
ONTAP Yes 
Oracle Cloud Infrastructure No 

Integrations

Hadoop Yes 
ONTAP No 
Oracle Cloud Infrastructure Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

$0.1344 per hour
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 Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

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

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Types of Training

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

Vendor Details

Company Name

NetApp

Founded

1992

Country

United States

Website

docs.netapp.com/us-en/ontap/concepts/mcc-config-concept.html

Vendor Details

Company Name

Oracle

Founded

1977

Country

United States

Website

www.oracle.com/big-data/big-data-service/

Product Features

Product Features

Big Data

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

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