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Azure Synapse Analytics VS Azure Data Factory

Compare Azure Synapse Analytics VS Azure Data Factory and see what are their differences

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  3. » Reviews
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Azure Synapse Analytics logo Azure Synapse Analytics

Get started with Azure SQL Data Warehouse for an enterprise-class SQL Server experience. Cloud data warehouses offer flexibility, scalability, and big data insights.

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.
  • Azure Synapse Analytics Landing page
    Landing page //
    2023-03-23
  • Azure Data Factory Landing page
    Landing page //
    2023-01-12

Azure Synapse Analytics features and specs

  • Integration
    Azure Synapse Analytics integrates with other Azure services like Azure Data Lake Storage, Power BI, and Azure Machine Learning, enabling seamless data movement and business intelligence processes.
  • Scalability
    It allows on-demand scalability, both horizontally and vertically, providing the flexibility to handle workloads of any size efficiently.
  • Unified Experience
    Offers a unified interface for data ingestion, preparation, management, and serving, simplifying data operations and reducing the need for multiple tools.
  • Advanced Security
    Includes robust security features like encryption, network protection, and advanced threat protection to ensure data security and compliance.
  • Serverless and Dedicated Options
    Provides both serverless and dedicated resource models, allowing businesses to optimize their costs by selecting the appropriate compute resources for their needs.

Possible disadvantages of Azure Synapse Analytics

  • Complexity
    The comprehensive range of features and tools can lead to a steep learning curve and complexity in setup and management for new users.
  • Cost Management
    Although flexibility is offered, managing and predicting costs can be challenging, especially in serverless scenarios where usage might fluctuate.
  • Resource Limitations
    Despite its scalability, there might be certain limitations in terms of data size or query complexity compared to some on-premises solutions.
  • Dependency on Internet Connectivity
    As a cloud-based solution, it requires stable and reliable internet connectivity, which may not be available in all regions or circumstances.
  • Integration Learning Curve
    While integration is a strength, mastering the integration with various Azure services and third-party tools can require substantial time and effort.

Azure Data Factory features and specs

  • Scalability
    Azure Data Factory can handle significant data volumes and allows for scaling up or down as needed, making it suitable for both small and complex data integration projects.
  • Integration
    It provides native integration with various Azure services and a wide array of connectors for different data sources, facilitating seamless data flow across platforms.
  • Cost-effective
    The pay-as-you-go pricing model enables cost management by aligning expenses with actual usage patterns, which can be beneficial for budget-conscious projects.
  • Ease of Use
    Offers a user-friendly interface with drag-and-drop features, making it accessible even for users with limited coding experience.
  • Security
    Azure Data Factory includes robust security features like network isolation, access management, and encryption both in-transit and at-rest, ensuring data protection.

Possible disadvantages of Azure Data Factory

  • Complexity
    Managing large and complex data pipelines may require a steep learning curve and expertise in Azure services, which could be a hindrance for non-technical users.
  • Debugging Challenges
    Debugging tasks and identifying error sources in complex ETL processes can be cumbersome, requiring detailed monitoring and analysis.
  • Limited On-Premise Integration
    While ADF offers numerous connectors, integration with certain on-premise data stores might still require additional configuration and setup.
  • Latency Issues
    Data transfer latency can occur when dealing with extremely large datasets or when integrating multiple cloud and on-premise sources.
  • Dependency on Cloud
    As a cloud-based service, performance can be impacted by internet connectivity issues, and consistent access to the cloud is necessary for operations.

Azure Synapse Analytics videos

+ Add

Azure Synapse Analytics - Next-gen Azure SQL Data Warehouse

More videos:

  • Review - Is Azure SQL Data Warehouse the Right SQL Platform for You?

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 Azure Synapse Analytics and Azure Data Factory)

Azure Synapse Analytics

Azure Data Factory

Office & Productivity
100 100%
Office & Productivity
0% 0
Data Integration
0 0%
Data Integration
100% 100
Development
100 100%
Development
0% 0
ETL
0 0%
ETL
100% 100

User comments

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Reviews

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

Azure Synapse Analytics Reviews

Data Warehouse Tools
Azure Synapse Analytics (formerly Azure Data Warehouse) is a cloud-native data warehouse integrated with other Azure services. It unifies data warehousing and big data analytics for comprehensive insights, offering visually interactive tools for user-friendly data exploration.
Source: peliqan.io
Top 6 Cloud Data Warehouses in 2023
Azure Synapse analytics is scalable for large data tables based on its distributed computing. It relies on the MPP (mentioned in the beginning, revisit if you did not grasp it) to quickly run high volumes of complex queries across multiple nodes. With Synapse, there’s an extra emphasis on security and privacy.
Source: geekflare.com
Top 5 BigQuery Alternatives: A Challenge of Complexity
Azure SQL Data Warehouse, now subsumed by Azure Synapse Analytics, brings together the worlds of big data analytics and enterprise data warehousing. Over the years, Azure has made a name for enabling the seamless transfer of data between on-premise and cloud ecosystems.
Source: blog.panoply.io

Azure Data Factory Reviews

Best ETL Tools: A Curated List
Azure Data Factory uses a pay-as-you-go pricing model based on several factors, including the number of activities performed, the duration of integration runtime hours, and data movement volumes. This flexible pricing allows for scaling based on workload but can lead to complex cost structures for larger or more complex data integration projects.
Source: estuary.dev
15+ Best Cloud ETL Tools
Azure Data Factory is a fully managed, serverless data integration service by Azure Cloud. You can easily connect to more than 90 built-in data sources without any added cost, allowing for efficient data integration at an enterprise level. Azure's visual platform lets you create ETL and ELT processes without having to write any code.
Source: estuary.dev
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

Azure Data Factory might be a bit more popular than Azure Synapse Analytics. We know about 4 links to it since March 2021 and only 4 links to Azure Synapse Analytics. 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.

Azure Synapse Analytics mentions (4)

  • DbVisualizer 24.2: A Complete Review
    Azure Synapse Analytics: DbVisualizer now has extended support for dedicated and serverless SQL pools in Azure Synapse Analytics. That includes support for database-scoped credentials, external file formats and data sources, and external tables. For more information, see the Azure Synapse Dedicated and Azure Synapse Serverless pages on the official site. - Source: dev.to / 9 months ago
  • Deploying a Data Warehouse with Pulumi and Amazon Redshift
    A data warehouse is a specialized database that's purpose built for gathering and analyzing data. Unlike general-purpose databases like MySQL or PostgreSQL, which are designed to meet the real-time performance and transactional needs of applications, a data warehouse is designed to collect and process the data produced by those applications, collectively and over time, to help you gain insight from it. Examples of... - Source: dev.to / over 2 years ago
  • [WSJ] Facebook Parent Meta Expected to Post Slowest Revenue Growth Since IPO
    You don't run into these kinds of problems with other tools, like the ones I mentioned. I've never tried the Azure ones, but my gut says they may have some scaling issues (synapse analytics looks promising but I have no experience with it). Source: about 3 years ago
  • The Difference Between Data Warehouses, Data Lakes, and Data Lakehouses.
    Popular managed cloud data warehouse solutions include Azure Synapse Analytics, Azure SQL Database, and Amazon Redshift. - Source: dev.to / about 3 years ago

Azure Data Factory mentions (4)

  • Choosing the right, real-time, Postgres CDC platform
    The major infrastructure providers offer CDC products that work within their ecosystem. Tools like AWS DMS, GCP Datastream, and Azure Data Factory can be configured to stream changes from Postgres to other infrastructure. - Source: dev.to / 6 months ago
  • (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 3 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 / about 4 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: about 4 years ago

What are some alternatives?

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

Saturn Cloud - ML in the cloud. Loved by Data Scientists, Control for IT. Advance your business's ML capabilities through the entire experiment tracking lifecycle. Available on multiple clouds: AWS, Azure, GCP, and OCI.

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”.

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

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.

Databricks Unified Analytics Platform - One platform for accelerating data-driven innovation across data engineering, data science & business analytics

Xplenty - Xplenty is the #1 SecurETL - allowing you to build low-code data pipelines on the most secure and flexible data transformation platform. No longer worry about manual data transformations. Start your free 14-day trial now.

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