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Iguazio

Iguazio

Overview

What is Iguazio?

Iguazio, headquartered in Herzliya, provides a Data Science Platform to automate machine learning pipelines. It aims to accelerate the development, deployment and management of AI applications at scale, enabling data scientists to focus on delivering better, more accurate and more…

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Recent Reviews
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Pricing

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What is Iguazio?

Iguazio, headquartered in Herzliya, provides a Data Science Platform to automate machine learning pipelines. It aims to accelerate the development, deployment and management of AI applications at scale, enabling data scientists to focus on delivering better, more accurate and more powerful…

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  • No setup fee

Offerings

  • Free Trial
  • Free/Freemium Version
  • Premium Consulting/Integration Services

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Product Demos

Iguazio and AWS FSx for NetApp ONTAP – DEMO

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Rapid Deployment of AI Applications using the Iguazio Data Science Platform on AWS Outpost (DEMO)

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Iguazio's Feature Store - Demo

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MLOPs World 2021 - Iguazio Product Demo

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MeatMe: Iguazio Demo

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Project Noodl - Iguazio Demo

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Product Details

What is Iguazio?

Iguazio Technical Details

Operating SystemsUnspecified
Mobile ApplicationNo
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Comparisons

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Reviews and Ratings

(3)

Reviews

(1-2 of 2)
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Douglas Carter | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Incentivized
Iguazio is a very powerful and reliable tool that i have used for over 3 years now. Being a MLOps Platform it has enabled us to develop, deploy and manage real-time AI applications at scale. The platform includes includes an online and offline feature store,fully integrated with automated model monitoring and drift detection, model serving and dynamic scaling capabilities.
  • It enables us to develop, deploy and manage real-time AI applications at scale.
  • Easy machine learning and rapidly deploy operational ML pipelines.
  • The user interface is not so much user-friendly, and easy-to-use, navigate.
With Iguazio we are able to scale up our organisations AI infrastructure which us vital to meet business goals and accelerate time-to-time. We are also able to manage our ML pipeline end-to-end using a full-stack,user-friendly environment, feature-rich integrated feature store and powerful data transformation and real-time feature engineering capabilities.
  • Real-time Data and Model pipeline.
  • Data + Model Monitoring.
  • Data ingestion and preparation.
Platform Connectivity (4)
97.5%
9.8
Connect to Multiple Data Sources
100%
10.0
Extend Existing Data Sources
100%
10.0
Automatic Data Format Detection
100%
10.0
MDM Integration
90%
9.0
Data Exploration (2)
95%
9.5
Visualization
90%
9.0
Interactive Data Analysis
100%
10.0
Data Preparation (4)
95%
9.5
Interactive Data Cleaning and Enrichment
100%
10.0
Data Transformations
90%
9.0
Data Encryption
90%
9.0
Built-in Processors
100%
10.0
Platform Data Modeling (4)
95%
9.5
Multiple Model Development Languages and Tools
100%
10.0
Automated Machine Learning
90%
9.0
Single platform for multiple model development
100%
10.0
Self-Service Model Delivery
90%
9.0
Model Deployment (2)
95%
9.5
Flexible Model Publishing Options
100%
10.0
Security, Governance, and Cost Controls
90%
9.0
  • Is a fully integrated solution with a user-friendly portal.
  • Manage our ML pipeline end-to-end using Full-stack,user friendly environment.
  • Iguazio enables our teams to manage all artefacts throughout their lifecycle.
  • Enhance team work and collaboration in our teams.
Iguazio provides a generic and easy to use mechanism to describe and track code,metadata,inputs and outputs of machine learning related tasks(executions). Users is able to track various elements, store them in a database and presents all running jobs as well as historical jobs in a single report. With Iguazio MLOps platform, data engineers,data scientist and MLOps engineers work in an unified environment with processes that increase productivity right out of the box.
Izaan Jivin | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Incentivized
It's a platform that enables you to develop and manage real-time AI applications at scale. A tool that provides data science, data engineering, and DevOps teams with one place to operationalize machine learning and rapidly deploy operational ML pipelines. It is fully integrated with automated model monitoring and drift detection capabilities.
  • Dynamic scaling capacity.
  • Central Metadata management.
  • Data ingestion and preparation.
  • No Cons for me. we are able to parallelize work within a single pod so that different workers can ingest data simultaneously.
  • Handling all types of triggers.
  • Model training and testing.
It is built in a way that supports low latency real-time data processing. The model can be triggered using different streaming engines without the need to write additional codes. It has serverless that enables developers to write code [that] automatically transform to auto-scaling production workload, significantly reducing time to market and resources.
  • Data connectors .
  • Feature store for engineering, storing,analyzing and storing all available features.
  • Enterprise management and support.
Platform Connectivity (4)
100%
10.0
Connect to Multiple Data Sources
100%
10.0
Extend Existing Data Sources
100%
10.0
Automatic Data Format Detection
100%
10.0
MDM Integration
100%
10.0
Data Exploration (2)
100%
10.0
Visualization
100%
10.0
Interactive Data Analysis
100%
10.0
Data Preparation (4)
100%
10.0
Interactive Data Cleaning and Enrichment
100%
10.0
Data Transformations
100%
10.0
Data Encryption
100%
10.0
Built-in Processors
100%
10.0
Platform Data Modeling (4)
100%
10.0
Multiple Model Development Languages and Tools
100%
10.0
Automated Machine Learning
100%
10.0
Single platform for multiple model development
100%
10.0
Self-Service Model Delivery
100%
10.0
Model Deployment (2)
100%
10.0
Flexible Model Publishing Options
100%
10.0
Security, Governance, and Cost Controls
100%
10.0
  • Is a fully integrated solution with a user friendly portal.
  • Offers great services for scalable data and feature engineering.
  • Has real-time pipelines.
  • Model tracking
Execution, experiment, data, model tracking, and automated deployment is done automatically through the MLRun serverless runtime engine. MLRun maintains a project hierarchy with strict membership and cross-team collaboration. End-to-end data governance is fully solidified and managed with authentication and identity management. Customers securely share data by providing access directly to it and not to copies.
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