Azure Data Lake Storage vs. Azure Synapse Analytics

Azure Data Lake is an absolutely essential piece of a modern data and analytics platform. Over the past 2 years, our usage of Azure Data Lake as a reporting source has continued to grow and far exceeds more traditional sources like MS SQL, Oracle, etc.

Incentivized

It's well suited for large, fastly growing, and frequently changing data warehouses (e.g., in startups). It's also suited for companies that want a single, relatively easy-to-use, centralized cloud service for all their data needs. Larger, more structured organizations could still benefit from this service by using Synapse Dedicated SQL Pools, knowing that costs will be much higher than other solutions. I think this product is not suited for smaller, simpler workloads (where an Azure SQL Database and a Data Factory could be enough) or very large scenarios, where it may be better to build custom infrastructure.

Incentivized

• Setting up Azure Data Lake Storage account, container is quite easy
• Access from anywhere and easy maintenance
• Integration with Azure Data Factory service for end to end pipeline is pretty easy
• Can store Any form of data (Structured, Unstructured, Semi) in faster manner

Incentivized

• Create data pipelines to connect with multiple data workspace(s) and external data
• Ability to connect with Azure Data Lake (sequentially) for data warehousing
• Being able to manage connections and create integration runtimes (for onPrem data capture)

Incentivized

• study for the certifications also to have them as a reference for work when you have any questions about applying a configuration to the equipment.
• The Internet interface is simple and easy to use. Capacity is good and it's good that HP continues to innovate with this technology

Incentivized

• It takes some time to setup a proper SQL Datawarehouse architecture. Without proper SSIS/automation scripts, this can be a very daunting task.
• It takes a lot of foresight when designing a Data Warehouse. If not properly designed, it can be very troublesome to use and/or modify later on.
• It takes a lot of effort to maintain. Businesses are continually changing. With that, a full time staff member or more will be required to maintain the SQL Data Warehouse.

Incentivized

The data warehouse portion is very much like old style on-prem SQL server, so most SQL skills one has mastered carry over easily. Azure Data Factory has an easy drag and drop system which allows quick building of pipelines with minimal coding. The Spark portion is the only really complex portion, but if there's an in-house python expert, then the Spark portion is also quiet useable.

Incentivized

Microsoft does its best to support Synapse. More and more articles are being added to the documentation, providing more useful information on best utilizing its features. The examples provided work well for basic knowledge, but more complex examples should be added to further assist in discovering the vast abilities that the system has.

Incentivized

Azure Data Lake Storage from a functionality perspective is a much easier solution to work with. It's implementation from Amazon EMR went smooth, and continued usage is definitely better. However, Amazon EMR was significantly cheaper overall between the high transaction fees and cost of storage due to growth. The two both have their advantages and disadvantages, but the functionality of Azure Data Lake Storage outweighed it's cost

Incentivized

When client is already having or using Azure then it’s wise to go with Synapse rather than using Snowflake. We got a lot of help from Microsoft consultants and Microsoft partners while implementing our EDW via Synapse and support is easily available via Microsoft resources and blogs. I don’t see that with Snowflake

Incentivized

Basically, the billing is predictable, and this all about it.

Incentivized

• Instead of having separate pools of storage for data we are now operating on a single layer platform which has cut down on time spent on maintaining those separate pools.
• We have had more of an ROI with the scalability as we are able to control costs of storage when need be.
• We are able to operate in a more streamlined approach as we are able to stay within the Azure suite of products and integrate seamlessly with the rest of the applications in our cloud-based infrastructure

Incentivized

• We have had an improvement in our overall processing time
• Cost was much lower than most of its competitors
• Our reporting needs have grown and housing the data here has been great

Incentivized