In the modern business world, data management and analytics are more crucial than ever. Nevertheless, since the amount of data that needs to be studied keeps growing, businesses need a mechanism to gather it all in one location so that it can be analyzed.
This is where contemporary cloud-based data warehousing and data management tools like Microsoft Azure Synapse and Snowflake come in. These are reputable data warehousing platforms that have received favourable customer reviews on Gartner Peer Reviews. Each one of them offers the quantity, velocity, and quality that business intelligence and analytics applications require.
But, there are just as many things in common as there are different. In many instances, the particular requirements of the data environment determine whether to use Snowflake or Microsoft Azure Synapse. Let’s analyze them both to discover which one performs better.
Major Differences Between Snowflake and Azure Synapse
Azure Synapse
Built on a solid SQL basis, Azure Synapse, formerly known as the Microsoft Azure SQL Data Warehouse, aims to offer a unified data analytics platform for big data systems and data warehouses.
Because of the huge parallel processing architecture used by Azure Synapse, its quick processing is not entirely dependent on pricy memory. To do this, it employs segments and clustered and non-clustered column store indexes that make it simpler to pinpoint the location and distribution of data.
Snowflake
For organized and semi-structured data, Snowflake is a relational database management system and analytics data warehouse. It is provided through a software-as-a-service (SaaS) model and makes use of a SQL database engine to control the way information is stored in the database and to process queries against virtual warehouses within the main warehouse, each of which is located in its own cluster node and does not share compute resources with any other nodes.
Cloud services for access restrictions, infrastructure management, querying, and authentication are built on top of this. Users of the Snowflake Elastic Data Warehouse can analyze and store data using resources from Amazon S3 or Azure.
For its features, which is the best?
Both are great performers, so it’s a tough call. Overall, Snowflake narrowly prevails for those seeking a premier data warehouse for analytics. Azure Synapse is a wise alternative for consumers who are pleased to work with Power BI, nonetheless.
Support and Usability of Azure Synapse and Snowflake
Azure Synapse
Because to Synapse’s reliance on SQL and Azure, a large number of users and developers worldwide are already familiar with both platforms. It is simple to utilize for them. There will frequently be little to no need for training.
Certain SQL syntax capabilities are not available, and there are no deduplication features for table storage, according to individuals who are experienced with SQL databases, and there are also no tools for converting code.
Snowflake
It is said that the Snowflake platform is user-friendly and has a straightforward SQL interface that makes it simple to set up and utilize. Also, Snowflake users can get support for any problems they might encounter thanks to 24/7 live support. Data vacuuming, compression, diagnostics, and other functions are all automated by Snowflake. Also, Snowflake eliminates the requirement for data duplication during scale-up operations. Furthermore, structured and semi-structured data are supported by Snowflake.
However, some customers claim that a lack of flexibility in areas like resizing might result in additional costs and prolonged maintenance times. Moreover, documentation is not always complete enough. And possibly the largest drawback is the absence of pre-built analytics tools.
Which Offers the Greatest Service and Usability?
Azure Synapse excels in terms of usability, although Snowflake isn’t far behind.
Snowflake vs. Azure Synapse: Security
Azure Synapse
To assist security teams in locating anomalous access points, SQL injection attacks, authentication attacks, and other threats, Azure Synapse provides data protection, access control, authentication, network security, and threat protection. Component isolation restrictions are additional security features.
Snowflake
In addition to network isolation and other strong security features, Snowflake promises always-on encryption.
It has different levels of security, and each level is more expensive. But, one benefit is that you avoid paying for security measures that you don’t require or desire.
Which One Has the Greatest Security?
Azure Synapse triumphs as a result of security being fully integrated and included in Synapse at no additional cost. While Snowflake provides a number of security capabilities that are helpful for companies trying to safeguard their data and data warehouses, many of these features are hidden behind more expensive pricing tiers, making them more expensive than Synapse’s built-in security measures.
Comparison between Snowflake and Azure Synapse
Azure Synapse
Microsoft has added integration tools like Data Factory for efforts to outcomes (ETO) and extract, load, transform (ELT) data migration to its conventional Azure SQL Data Warehouse in addition to Power BI for analytics. For the purpose of running notebooks, Synapse even includes Spark components such as Azure Spark Pools.
Also, Synapse integrates perfectly with every other Azure tool. For example, its Purview data cataloguing system is utilized for data governance. In order to prepare data for distribution to other users for analytics, this makes it simple to modify, curate, and clean it. Moreover, Purview makes it comparatively simple to trace data ancestry, consult table schema, and monitor data flow throughout the system.
Snowflake
While available on the AWS Marketplace, Snowflake is not completely integrated. Users occasionally mention that integrating Snowflake with other tools can be difficult. But, Snowflake also works nicely with other applications like Tableau, Apache Spark, IBM Cognos, and Qlik. Analysis will be simple for those employing these tools.
Which Has the Better Integration?
It is challenging to argue against the degree of integration if you reside within the Azure ecosystem. For instance, Power BI may be used in analytics with almost any effort at all. Except for those particular applications that Snowflake specifically targets, Azure Synapse triumphs.
Price comparison between Azure Synapse and Snowflake
Azure Synapse
Things become a little more complicated when it comes to Azure Synapse. It is priced as follows:
- The amount of data warehouse blocks and the duration in hours.
- The amount of processed and stored terabytes of data.
- Both the number and duration of Apache Spark Pool instances running.
- The volume of data movement operations, runtime, and cores utilized for data flow execution and debugging.
They are all combined into something called synaptic commit units (SCUs), which can be pre-purchased in accordance with a tiered structure and refers to “the amount of data that is copied from the source database to Azure Synapse Analytics.” But it is still complicated.
The quantity and frequency of data replication determine the number of SCUs that are used, according to Azure. In general, you’ll need more SCUs and pay more money to use Azure Synapse Analytics the more data you consume and store.
Snowflake
Compute and storage are kept apart in Snowflake’s pricing scheme. Concurrency scaling is automatically provided with no additional charge for all versions. With multiple versions starting at Basic and going higher, Snowflake pricing is somewhat complicated, with fees increasing as you move through the tiers. Snowflake costs about $40 per month, roughly.
Which Is the Best in Terms of Price?
A complete apples-to-apples comparison between Azure Synapse and Snowflake is challenging due to their differences. Yet, Snowflake triumphs because of its slightly less complicated pricing strategy. In spite of this, Azure Synapse triumphs if an analytics platform must be purchased as part of the deployment because Power BI is included at no additional cost.
Users are recommended to evaluate the resources they anticipate needing to support their expected data volume, quantity of processing, and their analysis requirements because price varies by use case. Snowflake will be less expensive for some users, while Azure Synapse will be more advantageous for others.
Choose Between Snowflake and Azure Synapse for Data Management
Excellent data warehouses and platforms for managing data, such as Azure Synapse and Snowflake, make it easier to store and analyze data.
Snowflake may be more adaptable to many use cases outside of the open-source and developer communities in some circumstances because of its ability to separate computation and storage cost. Depending on the platforms they employ, developers might also favour it. Because Snowflake focuses on such systems and technologies, businesses that frequently use Tableau, Apache Spark, IBM Cognos, and Qlik, for instance, could prefer it.
Yet for customers operating within the Azure ecosystem and conversant with SQL, Azure Synapse is ideally suited for data analysis. It can be challenging to outperform the terms provided by Microsoft in terms of total cost and substantial bundling reductions, even with Power BI being delivered for free to Azure and Microsoft 365 users.
Yet for customers operating within the Azure ecosystem and conversant with SQL, Azure Synapse is ideally suited for data analysis. It can be challenging to outperform the terms provided by Microsoft in terms of total cost and substantial bundling reductions, even with Power BI being delivered for free to Azure and Microsoft 365 users.
In conclusion, Azure Synapse likely prevails among less technical users. For users that just want to quickly deploy a good data warehouse and analytics platform without being constrained by setups, data science details, or manual setup, Azure Synapse is better suited. Therefore, it cannot be categorized as a simple tool or a tool for novices simply. Not at all.
For more affluent and higher-end users—and when the organization’s application mix favours its integration offerings—Snowflake wins. Moreover, Snowflake received a marginally better score on Gartner Peer Reviews. Also, consumers gave Snowflake greater ratings than Azure Synapse in the areas of scalability and flexibility. That shouldn’t be a problem for individuals who work in the Azure ecosystem. Scalability and customization restrictions must be taken into account by anyone developing a large-scale data warehouse and data management platform.
As is customary, the choice of platform, programming language, and prior vendor platform investment are the key factors in comparing such products.
