Azure Synapse vs. Data Factory - Key Differences and Features

Azure Synapse analytics provides a unified platform to businesses where they can explore, orchestrate, and visualize data. Businesses can also monitor data resources, allocate role-based data access, and write SQL/Spark codes. They can even integrate these codes with enterprise CI/CD processes.

While Azure Synapse helps businesses turn advanced analytics into actionable business insights, Azure Data Factory provides codeless data integration capabilities to businesses. Data Factory's cloud-based ETL services allow enterprises to create data-driven workflows. Using this platform, businesses can collate data from disparate stores. With Data Factory, you get access to services such as Azure HDInsight Hadoop, Azure Databricks, and Azure SQL Database.

In this article, let us delve deep into the features and the differences between Azure Synapse and Dada Factory platforms.

Azure Synapse vs. Data Factory - Key Features

Did you know that both ADF and Synapse have the same data integration engine and experiences which help create rich ETL pipelines? To understand the platforms better, let us take a closer look at their respective features -

Key Features of Microsoft Azure Synapse Analytics

1. Unified analytics platform

   • Data exploration
   • Data warehousing
   • Big data analytics
   • Machine learning tasks
   • Serverless and dedicated options

2. Serverless and dedicated options

   • Both data lake and data warehouse use cases
   • Cost-effective pricing option

3. Enterprise data warehousing

   • Critical data warehouse on industry-led SQL engine

4. Data lake exploration

   • Gathering relational and nonrelational data
   • Data warehousing solutions

5. Code-free hybrid data integration

   • Easy ETL/ELT processes
   • Code-free visual environment
   • Ingest data from 95 native connectors

6. Deeply integrated Apache Spark and SQL engines

   • Enhanced collaboration among
   • Easy T-SQL queries on data warehouse and Spark engines

7. Log and telemetry analytics

   • Industry-leading text-indexing technology
   • Insights from time-series, log, and telemetry data

8. Choice of language

   • Choices include T-SQL, KQL, Python, Scala, Spark SQL, and .Net

9. Integrated AI and BI

   • Deep integration of Azure Machine Learning, Cognitive Services, and Power BI

10. Cloud-native HTAP

    • Real-time transactional data stored in operational databases

Key Features of Azure Data Factory

1. Usability - Data Factory brings you easy SQL Server Integration Services (SSIS), in-built Git, and CI/CD support. On this platform, you can build ETL and ELT pipelines code-free with just a few clicks.

2. Cost-effective - Azure Data Factory offers scalable serverless cloud services, which come with a pay-as-you-go facility.

3. Powerful - Collate your on-prem enterprise data with 90 built-in connectors.

4. Intelligent - Data Factory is an intelligent intent-driven platform with autonomous ETL that facilities operational efficiencies and citizen integrators.

5. Hybrid Data Integration - Data Factory is fast, easy, and code-free. It simplifies the complexities and challenges of big data integration pipelines.

What are the differences between Azure Synapse and Data Factory?

To begin with, Azure Synapse is an analytics service, while Data Factory is a hybrid data integration service. Synapse brings together data warehousing and big data analysis. Data Factory simplifies ETL at scale. Azure Data Factory deployments allow developers to integrate disparate data sources, but Synapse offers a unified experience to manage, prepare, and serve data for BI and ML needs. Data Factory lacks reporting applications like Power BI and needs improvement in terms of speed and time. Whereas, in the case of Synapse, integration with 3rd party tools is difficult; it lacks adequate SQL support.

The Conclusion

To sum it up, Synapse and Data Factory are great platforms, each with its own unique features. Both the services have some similarities and dissimilarities; they have their set of individual pros and cons too. But understanding these two platforms is not enough. You need to understand your business needs too. After considering your business goals, you can decide which of these two platforms is the best for your organization. Can't seem to make up your mind? Consult a renowned software service provider today!

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