Average Ratings 0 Ratings
Average Ratings 0 Ratings
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
Hopsworks is a comprehensive open-source platform designed to facilitate the creation and management of scalable Machine Learning (ML) pipelines, featuring the industry's pioneering Feature Store for ML. Users can effortlessly transition from data analysis and model creation in Python, utilizing Jupyter notebooks and conda, to executing robust, production-ready ML pipelines without needing to acquire knowledge about managing a Kubernetes cluster. The platform is capable of ingesting data from a variety of sources, whether they reside in the cloud, on-premise, within IoT networks, or stem from your Industry 4.0 initiatives. You have the flexibility to deploy Hopsworks either on your own infrastructure or via your chosen cloud provider, ensuring a consistent user experience regardless of the deployment environment, be it in the cloud or a highly secure air-gapped setup. Moreover, Hopsworks allows you to customize alerts for various events triggered throughout the ingestion process, enhancing your workflow efficiency. This makes it an ideal choice for teams looking to streamline their ML operations while maintaining control over their data environments.
API Access
Has API
No
API Access
Has API
No
Integrations
Amazon EC2
No
Amazon Web Services (AWS)
No
Hadoop
Yes
IBM watsonx.data
No
Onehouse
No
Integrations
Amazon EC2
Yes
Amazon Web Services (AWS)
Yes
Hadoop
No
IBM watsonx.data
Yes
Onehouse
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
$1 per month
Free Trial
Yes
Free Version
Yes
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
No
Linux
Yes
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
Yes
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)
No
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
Yes
Vendor Details
Company Name
Apache Software Foundation
Country
United States
Website
gobblin.apache.org
Vendor Details
Company Name
Logical Clocks
Founded
2016
Country
Sweden
Website
www.logicalclocks.com/hopsworks
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
Product Features
Artificial Intelligence
Chatbot
No
For Healthcare
Yes
For Sales
No
For eCommerce
Yes
Image Recognition
No
Machine Learning
No
Multi-Language
No
Natural Language Processing
No
Predictive Analytics
Yes
Process/Workflow Automation
Yes
Rules-Based Automation
No
Virtual Personal Assistant (VPA)
No
Big Data
Collaboration
Yes
Data Blends
No
Data Cleansing
Yes
Data Mining
Yes
Data Visualization
Yes
Data Warehousing
Yes
High Volume Processing
Yes
No-Code Sandbox
No
Predictive Analytics
No
Templates
Yes
Data Analysis
Data Discovery
Yes
Data Visualization
Yes
High Volume Processing
Yes
Predictive Analytics
No
Regression Analysis
Yes
Sentiment Analysis
No
Statistical Modeling
No
Text Analytics
No
Data Management
Customer Data
Yes
Data Analysis
Yes
Data Capture
No
Data Integration
Yes
Data Migration
Yes
Data Quality Control
Yes
Data Security
Yes
Information Governance
No
Master Data Management
Yes
Match & Merge
No
Machine Learning
Deep Learning
Yes
ML Algorithm Library
Yes
Model Training
Yes
Natural Language Processing (NLP)
Yes
Predictive Modeling
Yes
Statistical / Mathematical Tools
Yes
Templates
Yes
Visualization
Yes