Azure Synapse and Databricks are two of the most popular data warehouse platforms that offer features of ETL pipelines, machine learning, and enterprise data warehousing. But when it comes to choosing the two platforms, it is up to the organization to assess its data management needs. This blog compares the two data warehouse platforms - azure synapse vs. databricks to help you choose the best one for your next big data project.
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Azure Synapse vs. Databricks - Comparison
Listed below are key points that help you understand the difference between Azure Synapse and Databricks to help you choose the right data warehouse platform for your next big data project.
Azure Synapse vs. Databricks: Overview
Azure Synapse is a limitless analytics service that combines big data analytics, data integration, and enterprise data warehousing into single unified platform. It comes with open-source Apache Spark and integrated support for .NET for Spark applications.
Databricks is a cloud-based data warehousing platform for processing, analyzing, storing, and transforming large amounts of data to build machine learning models.
Azure Synapse vs. Databricks: Pricing
The pricing of Azure Synapse is more complex. This is because it is charged based on data exploration, data warehousing, storage options such as the number of TBs stored and processed, data movement, runtime, and cores used in data flow execution and debugging.
When it comes to Databricks pricing, it is around $99 per month. There is also a free version available for this, and it may be less expensive for some users because storage is not included in the cost.
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Databricks vs. Azure Synapse: Architecture
Azure Synapse architecture consists of three components: Data storage, processing, and visualization integrated into a single platform.
When it comes to databricks architecture, it is not entirely a data warehouse. It works together with a LakeHouse architecture that combines the features of data warehouses and data lakes for metadata management and data governance.
Azure Synapse vs. Databricks: Machine Learning Development
Azure Synapse has built-in support for automating Machine Learning workflows. However, it does not offer complete Git support or a collaborative environment.
Databricks, on the other hand, incorporates streamlined ML workflows that give GPU-enabled clusters and substantial version control through Git.
Databricks vs. Azure Synapse: Programming Language Support
Azure Synapse supports programming languages such as Python, SQL, and Scala.
In contrast, Databricks supports Python, R, and SQL.
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Azure Synapse vs. Databricks: Data Security
Azure Synapse offers data protection, access control, authentication, network security, and threat protection to identify SQL injection attacks, unusual access locations, and authentication attacks.
Databricks, on the other hand, provide many more security features, including role-based access control (RBAC) and automated encryption. Thus, both platforms are effective in terms of data security.
Azure Synapse vs. Databrick: Notebook
Azure Synapse supports notebooks but does not support automated versions. The supported notebook is the Nteract Notebook, and one person must save the notebook before the other person can see the changes in Synapse.
On the other hand, Databrick supports both - notebooks and automated versioning features. The supported notebook is the Databricks notebook. In addition, databricks also offers real-time co-authoring with automatic version control.
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Azure Synapse vs. Databricks - A ShowDown of the Differences
Features | Azure Synapse | Databricks |
Overview | Azure Synapse is a limitless analytics service that combines big data analytics, data integration, and enterprise data warehousing into a single unified platform. It comes with open-source Apache Spark and integrated support for .NET for Spark applications. | Databricks is a cloud-based data warehousing platform for processing, analyzing, storing, and transforming a large amount of data to build machine learning models. |
Pricing | The pricing of Azure Synapse is more complex. This is because it is charged based on data exploration, data warehousing, storage options such as the number of TBs stored and processed, data movement, runtime, and cores used in data flow execution and debugging. | Databricks pricing is around $99 per month. There is also a free version available for this, and it may be less expensive for some users because storage is not included in its cost. |
Machine Learning Development | Azure Synapse has built-in support for automating Machine Learning workflows. However, it does not offer complete Git support or a collaborative environment. | Databricks, on the other hand, incorporates streamlined ML workflows that give GPU-enabled clusters and substantial version control through Git. |
Architecture | Azure Synapse architecture consists of three components: Data storage, processing, and visualization integrated into a single platform. | Databricks architecture is not entirely a data warehouse. It works together with a LakeHouse architecture that combines the best features of Data Lakes and Data Warehouses for metadata management and data governance. |
Programming Language Support | Azure Synapse supports programming languages such as Python, SQL, and Scala. | Databricks supports Python, R, and SQL. |
Data Security | Azure Synapse offers data protection, access control, authentication, network security, and threat protection to identify SQL injection attacks, unusual access locations, and authentication attacks. | Databricks, on the other hand, provide many more security features, including role-based access control (RBAC) and automated encryption. Thus, both platforms are effective in terms of data security. |
Notebook | Azure Synapse supports notebooks but does not support automated versions. The supported notebook is the Nteract Notebook. | Databrick supports both - notebooks and automated versioning features. The supported notebook is the Databricks notebook. |
When to use Azure Synapse vs. Databricks?
Comparing databricks synapse, it becomes clear when to use which data platform:
Use Azure Synapse when:
You need to create self-service reports through BI tools because power BI tools are easy to access directly from Synapse Studio.
You need to perform big data analytics, SQL data analytics, and data warehousing.
You are an SQL user who likes BI development with SQL technologies.
You want to quickly deploy a good data warehouse and analytics tool without a manual installation.
Use Databricks when:
You need to develop AI/ML applications in real-time scenarios and data science workloads.
You are a data scientist who uses a notebook and loves coding in Python or R.
There is more focus on data processing and data lake with familiarity with Apache Spark.
The data platform has a larger audience with better competencies.
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