Microsoft Azure Synapse Analytics vs Snowflake comparison

Microsoft Azure Synapse Analytics is an end-to-end analytics solution that successfully combines analytical services to merge big data analytics and enterprise data warehouses into a single unified platform. The solution can run intelligent distributed queries among nodes, and provides the ability to query both relational and non-relational data.

Microsoft Azure Synapse Analytics is built with these 4 components:

1. Synapse SQL
2. Spark
3. Synapse Pipeline
4. Studio

Microsoft Azure Synapse Analytics Features

Microsoft Azure Synapse Analytics has many valuable key features, including:

• Cloud Data Service: WIth Microsoft Azure Synapse Analytics you can operate services (data analytics, machine learning, data warehousing, dashboarding, etc.) in a single workspace via the cloud.
  
  
• Structured and unstructured data: Microsoft Azure Synapse Analytics supports both structured and unstructured data and allows you to manage relational and non-relational data - unlike data warehouses and lakes that tend to store them respectively.
  
  
• Effective data storage: Microsoft Azure Synapse Analytics offers next-level data storage with high availability and different tiers.
  
  
• Responsive data engine: Microsoft Azure Synapse Analytics uses Massive Parallel Processing (MPP) and is designed to handle large volumes of data and analytical workloads efficiently without any problems.
  
  
• Several scripting languages: The solution provides language compatibility and supports different programming languages, such as Python, Java, Spark SQL, and Scala.
  
  
• Query optimization: Microsoft Azure Synapse Analytics works well to facilitate limitless concurrency and performance optimization. It also simplifies workload management.

Microsoft Azure Synapse Analytics Benefits

Some of the benefits of using Microsoft Azure Synapse Analytics include:

• Database templates: Microsoft Azure Synapse Analytics offers industry-specific database templates that make it easy to combine and shape data.
  
  
• Better business insights: With Microsoft Azure Synapse Analytics you can expand discovery of insights from all your data and apply machine learning models to all your intelligent apps.
  
  
• Reduce project development time: Microsoft Azure Synapse Analytics makes it possible to have a unified experience for developing end-to-end analytics, which reduces project development time significantly.
  
  
• Eliminate data barriers: By using Microsoft Azure Synapse Analytics, you can perform analytics on operational and business apps data without data movement.
  
  
• Advanced security: Microsoft Azure Synapse Analytics provides both advanced security and privacy features to ensure data protection.
  
  
• Machine Learning: Microsoft Azure Synapse Analytics integrates Azure Machine Learning, Azure Cognitive Services, and Power BI.

Reviews from Real Users

Below are some reviews and helpful feedback written by Microsoft Azure Synapse Analytics users who are currently using the solution.

PeerSpot user Jael S., who is an Information Architect at Systems Analysis & Design Engineering, comments on her experience using the product, saying that it is “Scalable, intuitive, facilitates compliance and keeps your data secure”. She also says "We also like governance. It looks at what the requirements are for the company to identify the best way to ensure compliance is met when you move to the cloud."

Michel T., CHTO at Timp-iT, mentions that "the features most valuable are the simplicity, how easy it is to create a dashboard from different information systems."

A Senior Teradata Consultant at a tech services company says, "Microsoft provides both the platform and the data center, so you don't have to look for a cloud vendor. It saves you from having to deal with two vendors for the same task."

Snowflake is a cloud-based data warehousing solution for storing and processing data, generating reports and dashboards, and as a BI reporting source. It is used for optimizing costs and using financial data, as well as for migrating data from on-premises to the cloud. The solution is often used as a centralized data warehouse, combining data from multiple sources.

Snowflake has helped organizations improve query performance, store and process JSON and XML, consolidate multiple databases into one unified table, power company-wide dashboards, increase productivity, reduce processing time, and have easy maintenance with good technical support.

Its platform is made up of three components:

1. Cloud services - Snowflake uses ANSI SQL to empower users to optimize their data and manage their infrastructure, while Snowflake handles the security and encryption of stored data.
2. Query processing - Snowflake's compute layer is made up of virtual cloud data warehouses that let you analyze data through requests. Each of the warehouses does not compete for computing resources, nor do they affect the performance of each other.
3. Database storage - Snowflake automatically manages all parts of the data storage process, including file size, compression, organization, structure, metadata, and statistics.

Snowflake has many valuable vital features. Some of the most useful ones include:

• Snowflake architecture provides nearly unlimited scalability and high speed because it uses a single elastic performance engine. The solution also supports unlimited concurrent users and workloads, from interactive to batch.
• Snowflake makes automation easy and enables enterprises to automate data management, security, governance, availability, and data resiliency.
• With seamless cross-cloud and cross-region connections, Snowflake eliminates ETL and data silos. Anyone who needs access to shared secure data can get a single copy via the data cloud. In addition, Snowflake makes remote collaboration and decision-making fast and easy via a single shared data source.
• Snowflake’s Data Marketplace offers third-party data, which allows you to connect with Snowflake customers to extend workflows with data services and third-party applications.

There are many benefits to implementing Snowflake. It helps optimize costs, reduce downtime, improve operational efficiency, and automate data replication for fast recovery, and it is built for high reliability and availability.

Below are quotes from interviews we conducted with users currently using the Snowflake solution:

Sreenivasan R., Director of Data Architecture and Engineering at Decision Minds, says, "Data sharing is a good feature. It is a majorly used feature. The elastic computing is another big feature. Separating computing and storage gives you flexibility. It doesn't require much DBA involvement because it doesn't need any performance tuning. We are not doing any performance tuning, and the entire burden of performance and SQL tuning is on Snowflake. Its usability is very good. I don't need to ramp up any user, and its onboarding is easier. You just onboard the user, and you are done with it. There are simple SQL and UI, and people are able to use this solution easily. Ease of use is a big thing in Snowflake."

A director of business operations at a logistics company mentions, "It requires no maintenance on our part. They handle all that. The speed is phenomenal. The pricing isn't really anything more than what you would be paying for a SQL server license or another tool to execute the same thing. We have zero maintenance on our side to do anything and the speed at which it performs queries and loads the data is amazing. It handles unstructured data extremely well, too. So, if the data is in a JSON array or an XML, it handles that super well."

A Solution Architect at a wholesaler/distributor comments, "The ability to share the data and the ability to scale up and down easily are the most valuable features. The concept of data sharing and data plumbing made it very easy to provide and share data. The ability to refresh your Dev or QA just by doing a clone is also valuable. It has the dynamic scale up and scale down feature. Development and deployment are much easier as compared to other platforms where you have to go through a lot of stuff. With a tool like DBT, you can do modeling and transformation within a single tool and deploy to Snowflake. It provides continuous deployment and continuous integration abilities. There is a separation of storage and compute, so you only get charged for your usage. You only pay for what you use. When we share the data downstream with business partners, we can specifically create compute for them, and we can charge back the business."