Azure Synapse Analytics: A Comprehensive Guide For Data Professionals

Ronaldo vs. Messi- who is the better footballer? Oh, that’s tough! Synapse vs. other big 4 data warehouses is just like that. Azure Synapse is one of the best data warehouses which helps data engineers to have an entire end-to-end data pipeline in one place. 

As you might already know, the number of new businesses entering the IT sector is driving up demand for data storage, maintenance, and transfer between sites. You would need a good analytics service like Synapse that can handle all the business insights in less time. You wouldn’t need to spend on additional technology platforms to bring data from different sources into a single place. 

In this blog, I will walk you through the details of Azure Synapse Analytics including the features, working, and comparison with its competitors. 

Let’s dive in!

What is Azure Synapse Analytics?

Azure Synapse is an unlimited analytics solution that combines enterprise data warehousing and Big Data analytics. You have the flexibility to query data at scale utilizing serverless or dedicated resources, depending on your requirement. 

It is an advancement of Azure SQL Data Warehouse which is a robust relational database scaled up and hosted in the cloud. Advanced mashup and modeling capabilities are two features that are frequently used to aggregate data from numerous data sources, explain metrics, and maintain your data in a single, dependable tabular data model.

I will come to the details of the features later. Now, let’s take a look at:

That’s about it. So, I have been using the terms ‘Azure Synapse’ and ‘Azure Synapse Analytics’ interchangeably. Are they the same? 

What is the Difference Between Azure Synapse and Azure Synapse Analytics?

The difference between Azure Synapse and Azure Synapse Analytics is just in the terminology. Azure Synapse Analytics is the actual service that comes bundled with a lot of functionalities like Warehousing/ELT/Big Data. When we want to use it for storage/warehouse uses, we call it ‘Azure Synapse’ or even ‘Azure Synapse warehouse’, no hard rule on it.

In a data pipeline, we load data into the warehouse part of Synapse Analytics. A data pipeline is only concerned with the warehouse which we can call Azure Synapse.

To summarise it:

Azure Synapse Analytics =  Warehouse + ELT + Big Data services combined

Features of Azure Synapse Analytics

The main features of Azure Synapse Analytics are as follows:

• Azure Synapse provides cloud data warehousing, dashboarding, and machine learning analytics in a single workspace.
• It accepts any data type, including relational and non-relational data, and allows you to use SQL to analyze that data.
• Azure Synapse uses massively parallel processing ( MPP) database technology to gather and process enormous volumes of data and handle analytical tasks.
• You can use either an on-demand serverless deployment (which scales automatically as needed to handle any processing or load) or provided resources to query huge data repositories.
• Numerous programming languages, including Scala, Python, .Net, Java, R, SQL, T-SQL, and Spark SQL, are compatible with it.
• It enables simple integration with Azure Data Lake, Azure Blob Storage, and other Microsoft and Azure technologies.
• It includes the most recent security and privacy technologies like dynamic data masking, real-time data masking, always-on encryption, and Azure Active Directory authentication.

Next, let’s go over some use cases where Azure Synapse comes in handy.

Use Cases of Azure Synapse Analytics for Industries

• Financial sector: Azure Synapse enables the financial services sector to ensure data security. It also helps maintain a competitive edge by applying a cutting-edge approach to handling big data, data warehousing, and building individualized customer experiences. Azure is helpful for putting in place strong compliance and governance systems to protect consumer data as well.
• Manufacturing sector: Using Azure Synapse Analytics, the manufacturing service can gain scalable real-time insights. Real-time access to both fresh and historical data is made possible by Industry 4.0‘s integration of operational and analytical technology.
• Retail sector: You can mix data from several channels and receive real-time insights with an end-to-end analytics solution, which will help you better understand your customers and create a reliable supply chain. Companies like Canadian Tire Corporation (CTC) have used Synapse service for modernizing their data platform.
• Healthcare sector: The healthcare industry is under pressure from a scarcity of caregivers, legislative restrictions, and changing patient expectations. Azure Synapse Analytics helps to deliver personalized care, protect patient information, and empower care teams.

Do the benefits and industry use cases tempt you to opt for Azure Synapse Analytics? Then you should hold on! Because I’m going to present a comparison with its main competitors now. 

Azure Synapse Analytics vs. Competitors

	Snowflake	Redshift	BigQuery	Azure
Administration	Just need to select a cloud provider and virtual warehouse size.	Need to choose the right instance size and configure and scale nodes manually. Need AWS expertise.	Fully serverless and the provisioning is automatic.	Provides both serverless and dedicated options.
Scalability	Allows scaling storage and computation independently. Snowflake automatically updates nodes.	Decoupled storage and computing with RA3 nodes.	Storage and compute scale independently. Scaling is carried out automatically by BigQuery.	Automatic serverless option scaling. Need to add additional storage manually for the dedicated option.
Ingestion of streaming data	Possible with an added service. For continuous data ingestion, you can use Snowpipe	No, a built-in feature for this.	Feasible. You can code that calls the streaming API and inserts one record at a time.	Yes, you can make use of the Apache Spark streaming functionality in Azure Synapse.
Advantages	Writing and running the queries is easy.Enables you to save the table’s results in.csv format to your PC.	simple to use UI You can manage their data warehouses without in-depth technical expertise.It has a pay as you go strategy.It offers great security features (encryption and audit logging)	You can run extensive analytics without worrying about compatibility issues and transports data effortlessly between other systems. Simple to use, even by users who may not have much background in data analysis.It supports a large number of data types.Large volumes of data can be stored and analyzed without having to worry about running out of space. BigQuery has customizable pricing options	The ability to grant access on every level makes user management simple.We can import Power BI datasets into the workspace, which allows users to view everything in one location.
Disadvantages	It doesn’t support loading unstructured data	When dealing with a multi-tenant system, the inability to handle data across several partitions can occasionally be problematic. Even though storage has got quite inexpensive recently, storage costs are still very high.	It occasionally has high latency, particularly when querying extremely large datasets.BigQuery costs users for both storage and processing resourcesRunning a lot of queries that aren’t optimized or utilizing BigQuery for ad-hoc research might get pricey Only limited support for transactions and changes	Queries can take several minutes to run. Only the dedicated server pool offers to index.The only option available when importing Power BI datasets is to produce reports. Synapse restricts certain features and even consumes time

Conclusion

Azure Synapse is an analytics solution that combines enterprise data warehousing and Big Data analytics. You have the choice to query data at scale utilizing serverless or dedicated resources, as you see fit.  It helps financial services by guaranteeing data security. 

Synapse Analytics can significantly contribute to manufacturing, retail, and healthcare industries as well by providing useful insights from their data. Its main features include cloud data warehousing, dashboarding, and machine learning analytics are all provided by Azure Synapse in a single workspace. 

It also has security and privacy technologies like dynamic data masking, and real-time data masking. Now, to decide whether you need to opt for this, you can compare Azure Synapse Analytics with other alternatives available as given in the blog.

Meanwhile, you can enjoy a smooth ride with Hevo Data’s 150+ plug-and-play integrations (including 40+ free sources.) Hevo Data is helping thousands of customers take data-driven decisions through its no-code data pipeline solution. 

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