Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

A framework for distributed data integration that streamlines essential functions of Big Data integration, including data ingestion, replication, organization, and lifecycle management, is designed for both streaming and batch data environments. It operates as a standalone application on a single machine and can also function in an embedded mode. Additionally, it is capable of executing as a MapReduce application across various Hadoop versions and offers compatibility with Azkaban for initiating MapReduce jobs. In standalone cluster mode, it features primary and worker nodes, providing high availability and the flexibility to run on bare metal systems. Furthermore, it can function as an elastic cluster in the public cloud, maintaining high availability in this setup. Currently, Gobblin serves as a versatile framework for creating various data integration applications, such as ingestion and replication. Each application is usually set up as an independent job and managed through a scheduler like Azkaban, allowing for organized execution and management of data workflows. This adaptability makes Gobblin an appealing choice for organizations looking to enhance their data integration processes.

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

Docker
Ethereum
Filecoin
Hadoop
IPFS
Netdata

Integrations

Docker
Ethereum
Filecoin
Hadoop
IPFS
Netdata

Pricing Details

No price information available.
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

Apache Software Foundation

Country

United States

Website

gobblin.apache.org

Vendor Details

Company Name

IPFS Cluster

Website

cluster.ipfs.io

Product Features

Big Data

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

Product Features

Alternatives

Apache Spark Reviews

Apache Spark

Apache Software Foundation

Alternatives

Hadoop Reviews

Hadoop

Apache Software Foundation