Azure Data Factory vs. Azure Service Bus

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Azure Data Factory
Score 8.3 out of 10
N/A
Microsoft's Azure Data Factory is a service built for all data integration needs and skill levels. It is designed to allow the user to easily construct ETL and ELT processes code-free within the intuitive visual environment, or write one's own code. Visually integrate data sources using more than 80 natively built and maintenance-free connectors at no added cost. Focus on data—the serverless integration service does the rest.N/A
Azure Service Bus
Score 8.8 out of 10
N/A
Microsoft offers Azure Service Bus as a reliable cloud messaging as a service (MaaS) and simple hybrid integration solution.N/A
Pricing
Azure Data FactoryAzure Service Bus
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Azure Data FactoryAzure Service Bus
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeOptional
Additional Details——
More Pricing Information
Community Pulse
Azure Data FactoryAzure Service Bus
Top Pros
Top Cons
Features
Azure Data FactoryAzure Service Bus
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
Azure Data Factory
9.1
7 Ratings
10% above category average
Azure Service Bus
-
Ratings
Connect to traditional data sources9.27 Ratings00 Ratings
Connecto to Big Data and NoSQL9.07 Ratings00 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
Azure Data Factory
8.5
7 Ratings
2% above category average
Azure Service Bus
-
Ratings
Simple transformations9.27 Ratings00 Ratings
Complex transformations7.77 Ratings00 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
Azure Data Factory
7.7
7 Ratings
6% below category average
Azure Service Bus
-
Ratings
Data model creation8.45 Ratings00 Ratings
Metadata management7.56 Ratings00 Ratings
Business rules and workflow7.57 Ratings00 Ratings
Collaboration7.16 Ratings00 Ratings
Testing and debugging7.57 Ratings00 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
Azure Data Factory
7.7
7 Ratings
6% below category average
Azure Service Bus
-
Ratings
Integration with data quality tools7.47 Ratings00 Ratings
Integration with MDM tools8.07 Ratings00 Ratings
Best Alternatives
Azure Data FactoryAzure Service Bus
Small Businesses
Skyvia
Skyvia
Score 9.6 out of 10

No answers on this topic

Medium-sized Companies
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.2 out of 10
Anypoint Platform
Anypoint Platform
Score 8.2 out of 10
Enterprises
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.2 out of 10
Anypoint Platform
Anypoint Platform
Score 8.2 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Azure Data FactoryAzure Service Bus
Likelihood to Recommend
9.3
(7 ratings)
8.0
(1 ratings)
Support Rating
7.0
(1 ratings)
-
(0 ratings)
User Testimonials
Azure Data FactoryAzure Service Bus
Likelihood to Recommend
Microsoft
Well-suited Scenarios for Azure Data Factory (ADF): When an organization has data sources spread across on-premises databases and cloud storage solutions, I think Azure Data Factory is excellent for integrating these sources. Azure Data Factory's integration with Azure Databricks allows it to handle large-scale data transformations effectively, leveraging the power of distributed processing. For regular ETL or ELT processes that need to run at specific intervals (daily, weekly, etc.), I think Azure Data Factory's scheduling capabilities are very handy. Less Appropriate Scenarios for Azure Data Factory: Real-time Data Streaming - Azure Data Factory is primarily batch-oriented. Simple Data Copy Tasks - For straightforward data copy tasks without the need for transformation or complex workflows, in my opinion, using Azure Data Factory might be overkill; simpler tools or scripts could suffice. Advanced Data Science Workflows: While Azure Data Factory can handle data prep and transformation, in my experience, it's not designed for in-depth data science tasks. I think for advanced analytics, machine learning, or statistical modeling, integration with specialized tools would be necessary.
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Microsoft
If you need a cloud-based service bus or a simple to use queue/topic/routing/pub-sub service, then Azure Service Bus is a very good choice at a reasonable price and performance. Typically on-premise we'd use RabbitMQ because it "just works", but if you're building a "cloud-first" application, then this is the one to go with. It's especially easy to integrate with if you're already embedded in the Microsoft ecosystem.
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Pros
Microsoft
  • It allows copying data from various types of data sources like on-premise files, Azure Database, Excel, JSON, Azure Synapse, API, etc. to the desired destination.
  • We can use linked service in multiple pipeline/data load.
  • It also allows the running of SSIS & SSMS packages which makes it an easy-to-use ETL & ELT tool.
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Microsoft
  • Acting as a basic queuing service it works very well.
  • One of the best parts is that Azure Service Bus can work over HTTPS which helps in strict firewall situations. There is a performance hit if you choose to use HTTPS.
  • The routing capabilities are quite good when using topics and subscriptions. You can apply filters using a pseudo-SQL-like language though the correlation filters are quick and easy options.
  • Costs are very reasonable at low-ish volumes. If you're processing 10's of millions of messages a month... it may be a different story.
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Cons
Microsoft
  • Limited source/sink (target) connectors depending on which area of Azure Data Factory you are using.
  • Does not yet have parity with SSIS as far as the transforms available.
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Microsoft
  • The SqlFilter could be a little easier to use, but it's not terrible.
  • The performance while using HTTPS for the connection is a little slow compared to direct connections using AMQP ports.
  • There is a size limit to the message - unlike RMQ for instance, Azure Service Bus caps messages to 256kb on the standard tier.
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Support Rating
Microsoft
We have not had need to engage with Microsoft much on Azure Data Factory, but they have been responsive and helpful when needed. This being said, we have not had a major emergency or outage requiring their intervention. The score of seven is a representation that they have done well for now, but have not proved out their support for a significant issue
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Microsoft
No answers on this topic
Alternatives Considered
Microsoft
The easy integration with other Microsoft software as well as high processing speed, very flexible cost, and high level of security of Microsoft Azure products and services stack up against other similar products.
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Microsoft
RabbitMQ is simple and awesome... but so is Azure Service Bus. Both accomplish the same thing but in different environments. If you're building a cloud-native application - especially one that is serverless by design - Azure Service Bus is the only real choice in Azure. It works well, it's performance, and it's reasonably priced in the Standard tier. From our testing, RMQ is more performant, but it's hard to compare service-based implementations vs RMQ installed on VMs.
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Return on Investment
Microsoft
  • It is very useful and make things easier
  • Debugging can improve
  • Its better suited than other products with the same objective
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Microsoft
  • Compared to open-source free software like RMQ, Azure Service Bus does have some costs to it. But the cost is reasonable.
  • Also unlike RMQ, Azure Service Bus doesn't require you to stand up any hardware - so it's very easy to use and saves time/money from that perspective.
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ScreenShots