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Azure Synapse vs Databricks: Know The Important Difference

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May 26, 2022
Azure Synapse vs Databricks: Know The Important Difference

Data management is a very important factor in this digitalization era. It is very important for entrepreneurs to understand how to properly manage data. As we know, one of the challange in the making of Insight from big data is unstrucutred data that collected from various sources. It needs the proffesionals and expertises to monitoring and maintaining the data. Many big data platforms can be used for maintaining and processsing the data such as Azure Synapse from Microsoft and Databricks.

microsoft azure
img source azure.microsoft.com

Azure Synapse Analytics is a seamless data analytics service product that brings together enterprise SQL data warehousing and big data analytics services. It has modern features for managing big data, data warehousing, curating personalized customer experiences, and implementing effective compliance and governance practices to protect customer data. Get insightful information from all your data, across data warehouses, data lakes, operational databases, and big data analytics systems. Query relational and nonrelational data using the language of your choice to use.

Azure Synapse provides a seamless data analytics experience, here are some examples:

You can bring together data integration, enterprise data warehousing, and big data analytics together with Azure Synapse.

Efficient pipeline development
Easily create ETL and ELT processes without code in an intuitive environment or write your own code with over 95 native connectors.

Data set integration
Facilitates seamless collaboration via the integrated Apache Spark and SQL engine when using your language of choice such as T-SQL, Python, Spark, .NET.

Simplify security and management
Automate sensitive data protection in real time with column-level and row-level security and dynamic data hiding.

azure synapse
image source azure.microsoft.com

5 Advantages of Microsoft Azure Synapse Analytics

Limitless scale
Deliver insights from all your data, across data warehouses and big data analytics systems, with blazing speed.

Powerful insights
Expand discovery of insights from all your data and apply machine learning models to all your intelligent apps.

Unified experience
Significantly reduce project development time with a unified experience for developing end-to-end analytics solutions.

Converged analytics
Eliminate data barriers and perform analytics on operational and business apps data with Azure Synapse Link—no data movement.

Unmatched security
Secure data with the most advanced security and privacy features in the market, such as column- and row-level security and dynamic data masking.

If you need a data management app or are just interested in finding out more, you can start with 12 months of free service, 25+ services that are always free, and a USD200 credit.

Databricks

What is Databricks?

Just like Azure Synapse, Databricks is also a cloud-based data engineering tolls that allow you to do processing, transforming, and exploring the big volumes of data. Databricks now also supports in AWS, Microsoft Azure, and Google Cloud as the cloud partners. We also can accessed Databricks from Azure Portal as Azure Databricks is a jointly developed first-party service from Microsoft. Databricks combines data warehouses & data lakes into a lakehouse architecture. Collaborate on all of your data, analytics & AI workloads using one platform.

databricks
image source databricks.com

Why Use Databricks?

1. Unified Analytics Platform
Databricks have a Unified Analytics Platform (UAP), that accelerates innovation by unifying data science, engineering and business. Databricks has Lake house to do this function. The Databricks Lakehouse Platform combines the best elements of a data lake and data warehouse to deliver the reliability, robust governance, and performance of a data warehouse with the openness, flexibility, and machine learning support of the data lake.

2. Zero Management Cloud Platform.
Enable your team from various department to extract values from big data efficiently. The Data Analysts, Data Scientists, and Developers are provide highly available and performance optimized Spark clusters in a self-service fashion, allowing everyone to build and deploy advanced analytics applications with no DevOps expertise and always have access to the latest Spark features.

3. Multiclouds
With Databricks, we don't need to invest in reinventing processes on every cloud platform that we’re using to support data and AI efforts because in Databricks Lakehouse Platforms has a consistent management, security, and governance experience accross all clouds.

What is the Function of Databricks?

The Databricks Lakehouse Platform combines the best elements of a data lake and data warehouse to deliver the reliability, robust governance, and performance of a data warehouse with the openness, flexibility, and machine learning support of the data lake.

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