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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

    Azure Synapse Analytics

    Score7.4 out of 10
    N/AAzure Synapse Analytics is described as the former Azure SQL Data Warehouse, evolved, and as a limitless analytics service that brings together enterprise data warehousing and Big Data analytics. It gives users the freedom to query data using either serverless or provisioned resources, at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs.

    $4,700

    per month 5000 Synapse Commit Units (SCUs)

    Pricing
    Azure Data FactoryAzure Synapse Analytics
    Editions & Modules
    No answers on this topic
    Tier 1
    $4,700
    per month 5,000 Synapse Commit Units (SCUs)
    Tier 2
    $9,200
    per month 10,000 Synapse Commit Units (SCUs)
    Tier 3
    $21,360
    per month 24,000 Synapse Commit Units (SCUs)
    Tier 4
    $50,400
    per month 60,000 Synapse Commit Units (SCUs)
    Tier 5
    $117,000
    per month 150,000 Synapse Commit Units (SCUs)
    Tier 6
    $259,200
    per month 360,000 Synapse Commit Units (SCUs)
    Offerings
    Pricing Offerings
    Azure Data FactoryAzure Synapse Analytics
    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 Data FactoryAzure Synapse Analytics
    Considered Both Products
    Microsoft
    Chose Azure Data Factory
    Easier UI, Pipelines & Dataflows with various different sources.
    Incentivized
    Microsoft
    Chose Azure Synapse Analytics
    They're all part of the Microsoft Azure family, so they are not exactly competitors. They overlap in functionality, but they're targeted at different levels of customers.
    Azure Data Factory is an excellent stand-alone PaaS (included in Synapse Analytics) for writing, scheduling, …
    Incentivized
    Chose Azure Synapse Analytics
    Synapse, in comparison has its ups and downs against the competitors. However, where it excels, and builds it's markets is the cheaper costs (compared to Redshift), low code platforms and an in house solution that does not need you to leave the Synapse workspace for end to end …
    Incentivized
    Chose Azure Synapse Analytics
    When client is already having or using Azure then it’s wise to go with Synapse rather than using Snowflake. We got a lot of help from Microsoft consultants and Microsoft partners while implementing our EDW via Synapse and support is easily available via Microsoft resources and …
    Incentivized
    Key User Insights
    Would buy again
    100%
    Would buy again
    10 Answers
    80%
    Would buy again
    8 Answers
    Delivers good value for the price
    100%
    Delivers good value for the price
    10 Answers
    100%
    Delivers good value for the price
    10 Answers
    Happy with the feature set
    90%
    Happy with the feature set
    9 Answers
    80%
    Happy with the feature set
    8 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
    7 Answers
    Implementation went as expected
    100%
    Implementation went as expected
    10 Answers
    100%
    Implementation went as expected
    9 Answers
    Features
    Azure Data FactoryAzure Synapse Analytics
    Data Source Connection
    Comparison of Data Source Connection features of Azure Data Factory and Azure Synapse Analytics
    Feature
    Azure Data Factory
    8.5
    10 Ratings
    1% above category average
    Azure Synapse Analytics
    -
    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 Azure Synapse Analytics
    Feature
    Azure Data Factory
    7.8
    10 Ratings
    4% below category average
    Azure Synapse Analytics
    -
    Ratings
    Simple transformations8.710 Ratings00 Ratings
    Complex transformations7.010 Ratings00 Ratings
    Data Modeling
    Comparison of Data Modeling features of Azure Data Factory and Azure Synapse Analytics
    Feature
    Azure Data Factory
    6.2
    10 Ratings
    25% below category average
    Azure Synapse Analytics
    -
    Ratings
    Data model creation4.37 Ratings00 Ratings
    Metadata management5.48 Ratings00 Ratings
    Business rules and workflow5.910 Ratings00 Ratings
    Collaboration6.99 Ratings00 Ratings
    Testing and debugging6.310 Ratings00 Ratings
    Data Governance
    Comparison of Data Governance features of Azure Data Factory and Azure Synapse Analytics
    Feature
    Azure Data Factory
    5.6
    10 Ratings
    36% below category average
    Azure Synapse Analytics
    -
    Ratings
    Integration with data quality tools4.210 Ratings00 Ratings
    Integration with MDM tools7.09 Ratings00 Ratings
    Best Alternatives
    Azure Data FactoryAzure Synapse Analytics
    Small Businesses
    Skyvia
    Score10 out of 10
    No answers on this topic
    Medium-sized Companies
    IBM InfoSphere Information Server
    Score10 out of 10
    Snowflake
    Score8.7 out of 10
    Enterprises
    SolarWinds Task Factory
    Score8.3 out of 10
    Snowflake
    Score8.7 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Azure Data FactoryAzure Synapse Analytics
    Likelihood to Recommend
    7.3
    (10 ratings)
    7.7
    (12 ratings)
    Usability
    7.6
    (3 ratings)
    8.3
    (5 ratings)
    Support Rating
    7.0
    (1 ratings)
    9.6
    (2 ratings)
    Contract Terms and Pricing Model
    -
    (0 ratings)
    10.0
    (1 ratings)
    User Testimonials
    Azure Data FactoryAzure Synapse Analytics
    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
    Microsoft
    It's well suited for large, fastly growing, and frequently changing data warehouses (e.g., in startups). It's also suited for companies that want a single, relatively easy-to-use, centralized cloud service for all their data needs. Larger, more structured organizations could still benefit from this service by using Synapse Dedicated SQL Pools, knowing that costs will be much higher than other solutions. I think this product is not suited for smaller, simpler workloads (where an Azure SQL Database and a Data Factory could be enough) or very large scenarios, where it may be better to build custom infrastructure.
    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
    Microsoft
    • Quick to return data. Queries in a SQL data warehouse architecture tend to return data much more quickly than a OLTP setup. Especially with columnar indexes.
    • Ability to manage extremely large SQL tables. Our databases contain billions of records. This would be unwieldy without a proper SQL datawarehouse
    • Backup and replication. Because we're already using SQL, moving the data to a datawarehouse makes it easier to manage as our users are already familiar with SQL.
    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
    Microsoft
    • With Azure, it's always the same issue, too many moving parts doing similar things with no specialisation. ADF, Fabric Data Factory and Synapse pipeline serve the same purpose. Same goes for Fabric Warehouse and Synapse SQL pools.
    • Could do better with serverless workloads considering the competition from databricks and its own fabric warehouse
    • Synapse pipelines is a replica of Azure Data Factory with no tight integration with Synapse and to a surprise, with missing features from ADF. Integration of warehouse can be improved with in environment ETl tools
    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
    Microsoft
    The data warehouse portion is very much like old style on-prem SQL server, so most SQL skills one has mastered carry over easily. Azure Data Factory has an easy drag and drop system which allows quick building of pipelines with minimal coding. The Spark portion is the only really complex portion, but if there's an in-house python expert, then the Spark portion is also quiet useable.
    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
    Microsoft
    Microsoft does its best to support Synapse. More and more articles are being added to the documentation, providing more useful information on best utilizing its features. The examples provided work well for basic knowledge, but more complex examples should be added to further assist in discovering the vast abilities that the system has.
    Incentivized
    Read full review
    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
    Microsoft
    In comparing Azure Synapse to the Google BigQuery - the biggest highlight that I'd like to bring forward is Azure Synapse SQL leverages a scale-out architecture in order to distribute computational processing of data across multiple nodes whereas Google BigQuery only takes into account computation and storage.
    Incentivized
    Read full review
    Contract Terms and Pricing Model
    Microsoft
    No answers on this topic
    Microsoft
    Basically, the billing is predictable, and this all about it.
    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
    Microsoft
    • Licensing fees is replaced with Azure subscription fee. No big saving there
    • More visibility into the Azure usage and cost
    • It can be used a hot storage and old data can be archived to data lake. Real time data integration is possible via external tables and Microsoft Power BI
    Incentivized
    Read full review
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