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features
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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

IPFS Cluster enhances data management across a collection of IPFS daemons by managing the allocation, replication, and monitoring of a comprehensive pinset that spans multiple peers. While IPFS empowers users with content-addressed storage capabilities, the concept of a permanent web necessitates a solution for data redundancy and availability that preserves the decentralized essence of the IPFS Network. Serving as a complementary application to IPFS peers, IPFS Cluster maintains a unified cluster pinset and intelligently assigns its components to various IPFS peers. The peers in the Cluster create a distributed network that keeps an organized, replicated, and conflict-free inventory of pins. Users can directly ingest IPFS content to multiple daemons simultaneously, enhancing efficiency. Additionally, each peer in the Cluster offers an IPFS proxy API that executes cluster functions while mimicking the behavior of the IPFS daemon's API seamlessly. Written in Go, the Cluster peers can be launched and managed programmatically, making it easier to integrate into existing workflows. This capability empowers developers to leverage the full potential of decentralized storage solutions effectively.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Acquia CDP
Apache Spark
Docker
Ethereum
Filecoin
Galileo
Hadoop
IBM Cloud Object Storage
IPFS
Netdata
RadiantOne
Switch Automation

Integrations

Acquia CDP
Apache Spark
Docker
Ethereum
Filecoin
Galileo
Hadoop
IBM Cloud Object Storage
IPFS
Netdata
RadiantOne
Switch Automation

Pricing Details

$0.014 per hour
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

IBM

Founded

1911

Country

United States

Website

www.ibm.com/cloud/analytics-engine

Vendor Details

Company Name

IPFS Cluster

Website

cluster.ipfs.io

Product Features

Data Discovery

Contextual Search
Data Classification
Data Matching
False Positives Reduction
Self Service Data Preparation
Sensitive Data Identification
Visual Analytics

Data Visualization

Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery

Product Features

Alternatives

Alternatives

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