Azure Synapse vs Snowflake: 6 Key Differences

on ETL Tools • May 4th, 2021 • Write for Hevo

Many organizations are moving their data to the cloud. The reason is that companies have realized the benefits of storing their data in the cloud including reduced data storage costs, ease of access to data, access to Data Analytics tools, etc. However, most organizations find themselves at crossroads when making a decision on the modern Cloud Data Platform to go with. Azure Synapse and Snowflake are popular Cloud Data Solutions available to individuals and companies today. 

Both Synapse and Snowflake Analytics offer parallel processing capabilities to distribute the analysis of data across many nodes in the cloud. However, the two have a number of differences that can help you make a decision on which one suits your business needs. In this article, you will be exploring the topic Azure Synapse vs Snowflake based on 6 key metrics. You will also be looking at a few shortcomings of the two tools at the end of the article. 

Table of Contents

Introduction to Azure Synapse

Azure Synapse vs Snowflake: Azure Synapse logo
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Azure Synapse Analytics is an unlimited Data Analytics service that brings together Data Storage and Big Data Analysis. Azure Synapse offers a single workload for all workloads during data processing for immediate data prediction and Business Intelligence needs. This has been made possible by integration with Azure Machine Learning and Power BI and the ability of Azure Synapse to integrate mathematical Machine Learning models via the ONNX format. 

Azure Synapse gives its users the freedom to query huge volumes of data either on-demand serverless for ad hoc analysis and data exploration or with provisioned resources at scale. 

The benefits of Azure Synapse Analytics are as follows:

  • It offers full standard CSV support to user-controlled file selection.
  • Azure Synapse Analytics allows you to augment Data Lakes with IoT and Event Hubs for streaming in one centralized platform.
  • In comparison to other cloud providers, Azure Synapse Analytics is reportedly 14 times faster and costs 94% less.
Azure Synapse working
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Introduction to Snowflake

Snowflake logo
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Snowflake is a Data Warehouse-as-a-service platform built for the cloud. Its data architecture is different from that of Amazon Redshift because it uses the scalable, elastic Azure Blobs Storage as the internal storage engine and Azure Data Lake to store the unstructured, structured, and on-premise data ingested via the Azure Data Factory. 

The Snowflake Data Warehouse provides security and protection of data using Amazon S3 policy controls, SSO, Azure SAS tokens, and Google Cloud Storage access permissions. You can also scale your storage depending on your storage needs. 

The key benefit of leveraging Snowflake are as follows:

  • Given the elastic nature of the cloud, you can scale up your virtual warehouse to take advantage of extra compute resources to say run a high volume of queries, or load data faster.
  • With Snowflake you can combine semistructured and structured data for analysis and load it into the database without the need to transform or convert it into a fixed relational schema beforehand.
  • Snowflake has a multi-cluster architecture that takes care of concurrency issues like failures and delays.
  • Snowflake’s architecture enables companies leveraging it to seamlessly share data with any data consumer.
Snowflake with Azure working
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Simplify your Data Analysis with Hevo’s No-code Data Pipeline

A fully managed No-code Data Pipeline platform like Hevo helps you integrate data from 100+ data sources (including 30+ Free Data Sources) such as Azure Synapse and Snowflake in real-time in an effortless manner. Hevo with its minimal learning curve can be set up in just a few minutes allowing the users to load data without having to compromise performance. Its strong integration with umpteenth sources provides users with the flexibility to bring in data of different kinds, in a smooth fashion without having to code a single line. 

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  • Scalable Infrastructure: Hevo has in-built integrations for 100+ sources, that can help you scale your data infrastructure as required.
  • 24/7 Live Support: The Hevo team is available round the clock to extend exceptional support to you through chat, email, and support calls.
  • Schema Management: Hevo takes away the tedious task of schema management & automatically detects the schema of incoming data and maps it to the destination schema.
  • Live Monitoring: Hevo allows you to monitor the data flow so you can check where your data is at a particular point in time.

You can try Hevo for free by signing up for a 14-day free trial.

Understanding the Key Differences between Azure Synapse and Snowflake

The following are the key differences between Azure Synapse and Snowflake:

Azure Synapse vs Snowflake: PaaS vs SaaS

One of the major differences between the two is that they are sold differently. Snowflake is a SaaS (Software as a Service) platform that runs on top of Azure, Google Clouds, or AWS. It uses an abstraction layer to separate the Snowflake storage and compute credits that you pay for from the actual underlying compute cloud and storage. 

On the other hand, Azure Synapse is a PaaS (Platform as a Service) platform that comes with a free Azure Synapse Workspace development environment on top of the resources. Hence, you pay for the Azure resources. 

Azure Synapse vs Snowflake: Compute Resources

Each of the two platforms has a unique approach to compute resources. The two platforms allow their users to create SQL databases for Data Warehousing, but they act differently on those compute resources. 

The SQL databases created in Snowflake are completely decoupled from the compute resources that load or query those SQL databases. Due to this, any compute resource, known as a “warehouse” in Snowflake, can be used on any SQL database in Snowflake. 

Azure Synapse requires a dedicated SQL pool to create a long-lived SQL database that is good for Data Warehousing. 

Azure Synapse vs Snowflake: Cost

Snowflake has a Pay-As-You-go billing mechanism for computing which is calculated on a per-second basis. The minimum amount of time is 60 seconds with the ability to auto-suspend and auto-resume operations. So, if your query executes for 3 minutes, you will only pay for 3 minutes if the virtual Data Warehouse is suspended after the execution of the query. 

On the other hand, Snowflake charges compute on an hourly basis. So, if your Data Warehouse is only active for 12 hours in a month, you will only pay for the 12 hours for which the Data Warehouse existed. If the Data Warehouse is active for only 30 minutes, you will pay for 1 hour. 

Azure Synapse vs Snowflake: Scalability

Snowflake shines when it comes to scalability. This is because of its multi-cluster, shared data architecture. Snowflake allows you to isolate different workloads concurrently in a shared data layer. You can also create Virtual Warehouses for unlimited scale and concurrency and achieve your compute needs without downtime. 

Synapse offers both dedicated SQL pool and serverless SQL options. The former has a per-defined unit of scale (known as Data Warehouse Unit (DWU)) while the latter scales automatically to meet your scaling needs. 

Azure Synapse vs Snowflake: Administration

Snowflake is a SaaS platform whose goal is to achieve near-zero maintenance. Companies don’t need full-time Snowflake administrators since Snowflake Cloud Services provides capabilities such as automatic clustering, built-in performance optimization, and materialized view maintenance. 

With Azure Synapse, more administration is required around concurrency management and performance monitoring and tuning. 

Azure Synapse vs Snowflake: Interoperability with Azure Stack

The two platforms integrate well with Azure services such as Azure Data Factory, Azure Databricks, and Power BI. However, Azure Synapse Analytics shines in this area since it has enhancements whose task is to enhance interoperability within the Azure platform. 

Here is a brief summary of the differences between Azure Synapse and Snowflake to drive the point home.

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Limitations of Azure Synapse and Snowflake

The following are the cons associated with Azure Synapse:

  • A longer learning curve if you’re not experienced in using it. 
  • Azure Synapse does not support queries that run across databases. 
  • A lengthy setup process is involved. 

The following are the cons of Snowflake:

  • It is not suitable for use in some database use cases like online transactional processing) scenarios. 
  • Snowflake can be difficult to use for newbies. Its user interface is also not friendly. 
  • Most users and small companies find Snowflake too expensive for them. 

Conclusion

This blog talks about Azure Synapse vs Snowflake in great detail highlighting the 6 key differences between the two. These differences are depicted on the basis of mode of service, compute resources, scalability, cost, administration, and interoperability with the Azure Stack. The article wraps up the discussion with the drawbacks users face generally when leveraging Azure Synapse and Snowflake as a part of their workflow.

Extracting complex data from a diverse set of data sources can be a challenging task and this is where Hevo saves the day! Hevo offers a faster way to move data from Databases or SaaS applications into your Data Warehouse like Azure Synapse or Snowflake to be visualized in a BI tool of your choice. Hevo is fully automated and hence does not require you to code. You can try Hevo for free by signing up for a 14-day free trial. You can also have a look at the unbeatable pricing that will help you choose the right plan for your business needs.

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