Today, increasingly more firms are moving their data to the cloud because of the numerous benefits of doing so. These benefits include ease of access to data, reduced data storage costs, and access to analytics tools, among others. However, many firms face the tough decision on which modern cloud data platform is most suited for their needs. Snowflake and Azure Synapse are two of the very popular cloud data solutions that are available to businesses and individuals today.
The two (Synapse and Snowflake Analytics) are similar in that they offer parallel processing to distribute the data analysis across multiple nodes in the cloud. However, they also have many differences and understanding these can help you make the right decision on which cloud data platform is best for your needs.
However, to begin with, let's look at what the key features of Azure Synapse and Snowflake are.
This is an unlimited data analytics offering that brings the best of big data analysis and data storage together. If you are looking for a single workload during data processing for immediate business intelligence and data prediction needs, Azure Synapse Analytics is the way to go. Synapse is easily integrated with Power BI and Azure Machine Learning and can also provide machine learning capability through the ONNX format.
Some benefits of Azure Synapse Analytics are -
Snowflake differs from Synapse in that it is a data warehouse-as-a-service platform specifically created for the cloud. For the internal storage, it uses the elastic and scalable Azure Blobs Storage. It also uses Azure Data Lake to store the structured, on-premise, and unstructured data.
Some key benefits of using Snowflake are -
Now that we have an idea of these two cloud solutions, lets look at their differences.
Azure Synapse and Snowflake are sold and marketed differently. Azure Synapse is provided as a PaaS (Platform-as-a-Service) that comes with the robust and free Synapse Workspace environment that is a good capability on top of the other resources.
Snowflake, on the other hand, is sold as a SaaS (Software-as-a-Service). It runs on top of AWS, Google Cloud, or Azure. An abstraction layer is used to separate the compute credits and storage so that you only pay for them rather than the underlying storage and compute cloud.
These two platforms have a different approach to compute resources. However, both allow users to build SQL databases for things like data warehousing. With Azure Synapse, you require a dedicated SQL pool to create SQL databases for data warehousing.
SQL databases created in Snowflake, however, are fully separated from the compute resources required to query or load the SQL databases.
One key difference between the two platforms is their pricing model. Azure Synapse charges for the compute resources on an hourly basis while Snowflake provides a pay-as-you-go model. Snowflake's model is calculated on a per-second basis.
Snowflake's shared and multi-cluster data architecture makes it shine in terms of scalability. Azure Synapse, on the other hand, offers both Serverless SQL and dedicated SQL pools.
Flatworld Solutions is a leading provider of solutions to companies looking to leverage the many benefits of moving to the cloud. We have been providing software design and development services to a global clientele for over 18 years. Over the years, we have also gained significant knowhow and expertise in deploying data warehouse Azure, Azure Synapse, and Snowflake.
If you are looking for expert help to leverage all that the cloud has to offer, get in touch with us now.
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