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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Azure Data Factory

    Score8 out of 10
    N/AMicrosoft'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

    dbt

    Score9.2 out of 10
    N/Adbt is an SQL development environment, developed by Fishtown Analytics, now known as dbt Labs. The vendor states that with dbt, analysts take ownership of the entire analytics engineering workflow, from writing data transformation code to deployment and documentation. dbt Core is distributed under the Apache 2.0 license, and paid Teams and Enterprise editions are available.

    $0

    per month per seat

    Pricing
    Azure Data Factorydbt
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    Azure Data Factorydbt
    Free Trial
    NoYes
    Free/Freemium Version
    NoYes
    Premium Consulting/Integration Services
    NoYes
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Community Pulse
    Azure Data Factorydbt
    Considered Both Products
    Microsoft
    No answer on this topic
    dbt Labs
    No answer on this topic
    Key User Insights
    Would buy again
    100%
    Would buy again
    10 Answers
    100%
    Would buy again
    10 Answers
    Delivers good value for the price
    100%
    Delivers good value for the price
    10 Answers
    100%
    Delivers good value for the price
    9 Answers
    Happy with the feature set
    90%
    Happy with the feature set
    9 Answers
    100%
    Happy with the feature set
    10 Answers
    Lived up to sales and marketing promises
    89%
    Lived up to sales and marketing promises
    8 Answers
    100%
    Lived up to sales and marketing promises
    8 Answers
    Implementation went as expected
    100%
    Implementation went as expected
    10 Answers
    90%
    Implementation went as expected
    9 Answers
    Features
    Azure Data Factorydbt
    Data Source Connection
    Comparison of Data Source Connection features of Azure Data Factory and dbt
    Feature
    Azure Data Factory
    8.5
    10 Ratings
    1% above category average
    dbt
    -
    Ratings
    Connect to traditional data sources9.010 Ratings00 Ratings
    Connecto to Big Data and NoSQL8.110 Ratings00 Ratings
    Data Transformations
    Comparison of Data Transformations features of Azure Data Factory and dbt
    Feature
    Azure Data Factory
    7.8
    10 Ratings
    4% below category average
    dbt
    9.8
    8 Ratings
    19% above category average
    Simple transformations8.610 Ratings10.08 Ratings
    Complex transformations7.010 Ratings9.58 Ratings
    Data Modeling
    Comparison of Data Modeling features of Azure Data Factory and dbt
    Feature
    Azure Data Factory
    6.2
    10 Ratings
    25% below category average
    dbt
    9.1
    8 Ratings
    14% above category average
    Data model creation4.37 Ratings9.88 Ratings
    Metadata management5.48 Ratings8.88 Ratings
    Business rules and workflow5.910 Ratings9.08 Ratings
    Collaboration6.99 Ratings10.06 Ratings
    Testing and debugging6.410 Ratings8.08 Ratings
    Data Governance
    Comparison of Data Governance features of Azure Data Factory and dbt
    Feature
    Azure Data Factory
    5.6
    10 Ratings
    36% below category average
    dbt
    -
    Ratings
    Integration with data quality tools4.210 Ratings00 Ratings
    Integration with MDM tools7.09 Ratings00 Ratings
    Best Alternatives
    Azure Data Factorydbt
    Small Businesses
    Skyvia
    Score10 out of 10
    Skyvia
    Score10 out of 10
    Medium-sized Companies
    IBM InfoSphere Information Server
    Score10 out of 10
    IBM InfoSphere Information Server
    Score10 out of 10
    Enterprises
    SolarWinds Task Factory
    Score8.3 out of 10
    SolarWinds Task Factory
    Score8.3 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Azure Data Factorydbt
    Likelihood to Recommend
    7.3
    (10 ratings)
    10.0
    (10 ratings)
    Usability
    7.6
    (3 ratings)
    9.8
    (3 ratings)
    Support Rating
    7.0
    (1 ratings)
    -
    (0 ratings)
    User Testimonials
    Azure Data Factorydbt
    Likelihood to Recommend
    Microsoft
    Best scenario is for ETL process. The flexibility and connectivity is outstanding. For our environment, SAP data connectivity with Azure Data Factory offers very limited features compared to SAP Data Sphere. Due to the limited modelling capacity of the tool, we use Databricks for data modelling and cleaning. Usage of multiple tools could have been avoided if adf has modelling capabilities.
    Incentivized
    Read full review
    dbt Labs
    The prerequisite is that you have a supported database/data warehouse and have already found a way to ingest your raw data. Then dbt is very well suited to manage your transformation logic if the people using it are familiar with SQL. If you want to benefit from bringing engineering practices to data, dbt is a great fit. It can bring CI/CD practices, version control, automated testing, documentation generation, etc. It is not so well suited if the people managing the transformation logic do not like to code (in SQL) but prefer graphical user interfaces.
    Incentivized
    Read full review
    Pros
    Microsoft
    • Data Ingestion - it works very well with numerous data sources.
    • Data pipeline orchestration: It is a generic, popular tool for orchestrating data pipelines.
    • Works well in Azure ecosystem, Azure services and data platforms like Databricks.
    • It is a serverless and scalable solution for cloud data integration.
    Incentivized
    Read full review
    dbt Labs
    • dbt supports version control through GIT, this allows teams to collaborate and track the data transformation logic.
    • dbt allows us to build data models which helps to break complex transformation logic into simple and smaller logic.
    • dbt is completely based on SQL which allows data analyst and data engineers to build the transformation logic.
    • dbt can be easily integrated with snowflake.
    Incentivized
    Read full review
    Cons
    Microsoft
    • Granularity of Errors: Sometimes, Azure Data Factory provides error messages that are too generic or vague for us, making it challenging to pinpoint the exact cause of a pipeline failure. Enhanced error messages with more actionable details would greatly assist us as users in debugging their pipelines.
    • Pipeline Design UI: In my experience, the visual interface for designing pipelines, especially when dealing with complex workflows or numerous activities, can become cluttered. I think a more intuitive and scalable design interface would improve usability. In my opinion, features like zoom, better alignment tools, or grouping capabilities could make managing intricate designs more manageable.
    • Native Support: While Azure Data Factory does support incremental data loads, in my experience, the setup can be somewhat manual and complex. I think native and more straightforward support for Change Data Capture, especially from popular databases, would simplify the process of capturing and processing only the changed data, making regular data updates more efficient
    Incentivized
    Read full review
    dbt Labs
    • Field-level lineage (currently at table level)
    • Documentation inheritance - if a field is documented the downstream field of the same name could inherit the doc info
    • Adding python model support (in beta now)
    Incentivized
    Read full review
    Usability
    Microsoft
    So far product has performed as expected. We were noticing some performance issues, but they were largely Synapse related. This has led to a shift from Synapse to Databricks. Overall this has delayed our analytic platform. Once databricks becomes fully operational, Azure Data Factory will be critical to our environment and future success.
    Incentivized
    Read full review
    dbt Labs
    dbt is very easy to use. Basically if you can write SQL, you will be able to use dbt to get what you need done. Of course more advanced users with more technical skills can do more things.
    Incentivized
    Read full review
    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
    Incentivized
    Read full review
    dbt Labs
    No answers on this topic
    Alternatives Considered
    Microsoft
    Azure Data Factory helps us automate to schedule jobs as per customer demands to make ETL triggers when the need arises. Anyone can define the workflow with the Azure Data Factory UI designer tool and easily test the systems. It helped us automate the same workflow with programming languages like Python or automation tools like ansible. Numerous options for connectivity be it a database or storage account helps us move data transfer to the cloud or on-premise systems.
    Incentivized
    Read full review
    dbt Labs
    I actually don't know what the alternative to dbt is. I'm sure one must exist other than more 'roll your own' options like Apache Airflow, say, bu tin terms of super easy managed/cloud data transforms, dbt really does seem to be THE tool to use. It's $50/month per dev, BUT there's a FREE version for 1 dev seat with no read-only access for anyone else, so you can always start with that and then buy yourself a seat later.
    Incentivized
    Read full review
    Return on Investment
    Microsoft
    • Facilitate better decision-making and improve business processes.
    • Optimize business process outcomes by increasing internal efficiency and operational effectiveness.
    • Boosts revenue growth while improving business process agility.
    Incentivized
    Read full review
    dbt Labs
    • Simplified our BI layer for faster load times
    • Increased the quality of data reaching our end users
    • Makes complex transformations manageable
    Incentivized
    Read full review
    ScreenShots