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Diyotta VS Azure Data Factory

Compare Diyotta VS Azure Data Factory and see what are their differences

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Diyotta logo Diyotta

Enterprise Data Integration For All.

Azure Data Factory logo Azure Data Factory

Learn more about Azure Data Factory, the easiest cloud-based hybrid data integration solution at an enterprise scale. Build data factories without the need to code.
  • Diyotta Landing page
    Landing page //
    2021-10-26

Diyotta is an enterprise-class data integration platform that connects enterprises to all their data. It provides a single integrated platform that makes it easy to quickly and efficiently integrate enormous volumes of data from any source to any target, whether on-premises, in the cloud, or a hybrid environment. Diyotta is built for modern data architectures where data can be processed in batch, or real-time streams, in the most optimized fashion. It also scales in all dimensions with its agent-based architecture and optimizes the data movement across several data-points easily and efficiently.

Diyotta accelerates time to value for new investments in big data platforms and ongoing modernization of data warehouses. With Diyotta, companies fully leverage their existing platform investment, move to modern data platforms with the highest level of reuse possible, and quickly respond to business needs for new data and analytics.

  • Azure Data Factory Landing page
    Landing page //
    2023-01-12

Diyotta

Website
diyotta.com
Pricing URL
Official Diyotta Pricing
$ Details
Free Trial $100.0 / Monthly (100 Credits)
Release Date
2011 October
Edit details

Azure Data Factory

Website
azure.microsoft.com
Pricing URL
-
$ Details
-
Release Date
-
Edit details

Diyotta videos

+ Add

CloudSync Product Demo

More videos:

  • Review - Customer Testimonial - Clearsense
  • Tutorial - Data Pipelines In Minutes Using Data Movement Wizard
  • Review - ELT using Diyotta
  • Review - Diyotta | Leading The Modern Data Integration Movement

Azure Data Factory videos

+ Add

Azure Data Factory Tutorial | Introduction to ETL in Azure

More videos:

  • Review - Use Azure Data Factory to copy and transform data
  • Review - Pass summit 2019: Head to Head, SSIS Versus Azure Data Factory

Category Popularity

0-100% (relative to Diyotta and Azure Data Factory)

Diyotta

Azure Data Factory

Development
100 100%
Development
0% 0
ETL
0 0%
ETL
100% 100
Backup & Sync
100 100%
Backup & Sync
0% 0
Data Integration
0 0%
Data Integration
100% 100

User comments

Share your experience with using Diyotta and Azure Data Factory. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Diyotta and Azure Data Factory

Diyotta Reviews

The 28 Best Data Integration Tools and Software for 2020
Description: Diyotta is a unified data integration platform that integrates with modern data lake and data warehousing environments. The drag-and-drop user interface and native processing capabilities make this product one to consider. Diyotta enables shorter development times, faster data movement, and reusability across the enterprise to make future development simple....
Source: solutionsreview.com

Azure Data Factory Reviews

Top 8 Apache Airflow Alternatives in 2024
While Apache Airflow focuses on creating tasks and building dependencies between them for workflow automation, Azure Data Factory is suitable for integration tasks. It would be a perfect fit for the construction of the ETL and ELT pipelines for data migration and integration across platforms.
Source: blog.skyvia.com
A List of The 16 Best ETL Tools And Why To Choose Them
Azure Data Factory is a cloud-based ETL service offered by Microsoft used to create workflows that move and transform data at scale.
Source: www.datacamp.com
Top Big Data Tools For 2021
Azure Data Factory is a cloud solution that enables you to integrate data between multiple relational and non-relational sources, transforming it according to your objectives and requirements.
Source: blog.bismart.com

Social recommendations and mentions

Based on our record, Azure Data Factory seems to be more popular. It has been mentiond 3 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Diyotta mentions (0)

We have not tracked any mentions of Diyotta yet. Tracking of Diyotta recommendations started around Mar 2021.

Azure Data Factory mentions (3)

  • (Recommend) Fun Open Source Tool for Pushing Data Around
    You might want to look at Azure Data Factory https://azure.microsoft.com/en-us/services/data-factory/ to extend SSIS EDIT: Yes, I missed the "open source" part :). Source: about 2 years ago
  • Deploying Azure Data Factory using Bicep
    I'm also planning to do more content with Azure Data Factory, so I'd thought it be good to make a video combining the two. - Source: dev.to / almost 3 years ago
  • Class construction help
    Or, if oyu are using azure then azure data factory https://azure.microsoft.com/en-us/services/data-factory/. Source: almost 3 years ago

What are some alternatives?

When comparing Diyotta and Azure Data Factory, you can also consider the following products

Striim - Striim provides an end-to-end, real-time data integration and streaming analytics platform.

Apache NiFi - An easy to use, powerful, and reliable system to process and distribute data.

HVR - Your data. Where you need it. HVR is the leading independent real-time data replication solution that offers efficient data integration for cloud and more.

Workato - Experts agree - we're the leader. Forrester Research names Workato a Leader in iPaaS for Dynamic Integration. Get the report. Gartner recognizes Workato as a “Cool Vendor in Social Software and Collaboration”.

Celigo Data Loader - Celigo is an advanced platform that comes with exclusive service data loading in a smooth and effective way.

DataTap - Adverity is the best data intelligence software for data-driven decision making. Connect to all your sources and harmonize the data across all channels.

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