Azure Databricks vs. Iguazio

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Azure Databricks
Score 8.7 out of 10
N/A
Azure Databricks is a service available on Microsoft's Azure platform and suite of products. It provides the latest versions of Apache Spark so users can integrate with open source libraries, or spin up clusters and build in a fully managed Apache Spark environment with the global scale and availability of Azure. Clusters are set up, configured, and fine-tuned to ensure reliability and performance without the need for monitoring. The solution includes autoscaling and auto-termination to improve…N/A
Iguazio
Score 10.0 out of 10
N/A
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 solutions instead of spending their time on infrastructure. The platform is open and deployable anywhere - multi-cloud, on prem or edge. The vendor states Iguazio powers real-time data science applications for…N/A
Pricing
Azure DatabricksIguazio
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Azure DatabricksIguazio
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Azure DatabricksIguazio
Features
Azure DatabricksIguazio
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Azure Databricks
8.1
Ratings
3% below category average
Iguazio
9.9
Ratings
17% above category average
Connect to Multiple Data Sources6.20 Ratings10.00 Ratings
Extend Existing Data Sources9.00 Ratings10.00 Ratings
Automatic Data Format Detection9.00 Ratings10.00 Ratings
MDM Integration8.00 Ratings9.50 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Azure Databricks
6.4
Ratings
27% below category average
Iguazio
9.7
Ratings
15% above category average
Visualization5.90 Ratings9.50 Ratings
Interactive Data Analysis6.90 Ratings10.00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Azure Databricks
8.0
Ratings
2% below category average
Iguazio
9.7
Ratings
17% above category average
Interactive Data Cleaning and Enrichment7.00 Ratings10.00 Ratings
Data Transformations9.00 Ratings9.50 Ratings
Data Encryption9.00 Ratings9.50 Ratings
Built-in Processors7.10 Ratings10.00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Azure Databricks
8.3
Ratings
1% below category average
Iguazio
9.7
Ratings
15% above category average
Multiple Model Development Languages and Tools8.10 Ratings10.00 Ratings
Automated Machine Learning9.00 Ratings9.50 Ratings
Single platform for multiple model development8.00 Ratings10.00 Ratings
Self-Service Model Delivery8.00 Ratings9.50 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Azure Databricks
8.5
Ratings
0% below category average
Iguazio
9.7
Ratings
13% above category average
Flexible Model Publishing Options8.00 Ratings10.00 Ratings
Security, Governance, and Cost Controls9.00 Ratings9.50 Ratings
Best Alternatives
Azure DatabricksIguazio
Small Businesses
Jupyter Notebook
Jupyter Notebook
Score 9.4 out of 10
Jupyter Notebook
Jupyter Notebook
Score 9.4 out of 10
Medium-sized Companies
Posit
Posit
Score 10.0 out of 10
Posit
Posit
Score 10.0 out of 10
Enterprises
Posit
Posit
Score 10.0 out of 10
Posit
Posit
Score 10.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Azure DatabricksIguazio
Likelihood to Recommend
9.8
(0 ratings)
10.0
(0 ratings)
Usability
8.0
(0 ratings)
-
(0 ratings)
User Testimonials
Azure DatabricksIguazio
Likelihood to Recommend
Having access to all databases and tables in one place is what has helped me and my team to function better. The in built functionality/access to SQL and Python is definitely an added bonus! The icing on the cake is the ability to export your data into an Excel spreadsheet for additional analysis. If you have less to no working knowledge of SQL or Python, its better to look at alternatives.
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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.
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Pros
  • Consistently great performance when dealing with huge scale data with the help of spark architecture
  • Magic commands such as spark sql, pyspark, scala . This comes really handy in day to day work
  • Integration with other Azure services is super smooth and robust
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  • Dynamic scaling capacity.
  • Central Metadata management.
  • Data ingestion and preparation.
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Cons
  • Intuitive interface
  • Ease of use
  • Providing FAQ or QRGs
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  • The user interface is not so much user-friendly, and easy-to-use, navigate.
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Usability
Based on my extensive use of Azure Databricks for the past 3.5 years, it has evolved into a beautiful amalgamation of all the data domains and needs. From a data analyst, to a data engineer, to a data scientist, it jas got them all! Being language agnostic and focused on easy to use UI based control, it is a dream to use for every Data related personnel across all experience levels!
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Alternatives Considered
Against all the tools I have used, Azure Databricks is by far the most superior of them all! Why, you ask? The UI is modern, the features are never ending and they keep adding new features. And to quote Apple, "It just works!" Far ahead of the competition, the delta lakehouse platform also fares better than it counterparts of Iceberg implementation or a loosely bound Delta Lake implementation of Synapse
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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.
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Return on Investment
  • The support team is amazing, they help you at every stage of the projects, from sales to delivery.
  • On a framework level, it has had an amazing impact and has reduced the clients overall data platform costs by a staggering 65%
  • There has been a 40% Manual work requirement on average for the clients when they move to Azure Databricks Data Platform
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  • 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.
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ScreenShots