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What is Zettar zx?

Zettar zx - Optimized Data Migration and Transfer Solutions Application Scenarios • Data Synchronization and Replication • Seamless Data Migration • Dynamic Tiering Solutions • Migration within Cloud Environments • Movement of Data in Hybrid Cloud Settings • Centralizing Data for AI and Analytical Applications • Collection of Data for Autonomous Vehicles • Persistent Workloads from Edge to Core and Edge to Cloud • Backup and Recovery Solutions for Data • Temporary Data Staging • Handling Data Transfers at Petabyte Scale and Managing Billions of Files • Forwarding and Transferring Data • Real-time Data Streaming Capabilities Distinctive Features • Peer-to-Peer Scalable Architecture: Achieving rapid data transfer through parallel computing at the cluster level. • Built-in Transparent Compression • Compatibility with Ethernet and InfiniBand Technologies. • Supports a variety of data types, including files and objects (with S3 AWS compatibility) and S3 multipart APIs. • Capability for simultaneous sending and receiving, allowing distinct areas for data reading and writing. • High Security and Reliability: Utilizing TLS encryption to safeguard data transmission • Comprehensive SDK and API for Integration • Accessible via Web Interface Zettar zx not only enhances the efficiency of data migration and transfer processes but also ensures that users benefit from state-of-the-art security and seamless integration.

What is IPFS Cluster?

IPFS Cluster significantly improves data management across a network of IPFS daemons by overseeing the allocation, replication, and monitoring of a robust pinset that spans various peers. As IPFS offers users the ability to utilize content-addressed storage, the need for a permanent web brings forth the requirement for solutions that ensure data redundancy and availability while maintaining the decentralized nature of the IPFS Network. Acting as a complementary tool for IPFS peers, IPFS Cluster sustains a cohesive cluster pinset and smartly distributes its elements among different IPFS peers. The peers forming the Cluster establish a distributed network that upholds an organized, replicated, and conflict-free record of pins, ensuring reliability. Users can efficiently ingest IPFS content to multiple daemons at once, thereby boosting operational effectiveness. Furthermore, each peer within the Cluster provides an IPFS proxy API that carries out cluster functions while seamlessly imitating the behavior of the API from the IPFS daemon. Built using Go, the Cluster peers can be initiated and overseen programmatically, facilitating easier integration into current workflows. This feature empowers developers to tap into the complete capabilities of decentralized storage solutions, ultimately enhancing their projects' functionality and resilience. Additionally, the innovative design of IPFS Cluster fosters collaboration among users and developers alike, creating a more robust ecosystem for decentralized applications.

Media

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Media

Integrations Supported

Docker
Ethereum
Filecoin
IPFS
Netdata

Integrations Supported

Docker
Ethereum
Filecoin
IPFS
Netdata

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Zettar

Date Founded

2015

Company Location

United States

Company Website

zettar.com

Company Facts

Organization Name

IPFS Cluster

Company Website

cluster.ipfs.io

Categories and Features

Data Management

Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge

Categories and Features

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