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Limitless analytics service with unmatched time to insight (formerly SQL Data Warehouse)

  • Pros

  • All data services in one place
  • Single unified user experience
  • Easy to get started
  • Great language support
  • Industry standards
  • Good integration between services
  • Provisioned and serverless compute options
  • Active product group
  • Strong product roadmap
  • Cons

  • In public preview
  • Missing DevOps features (coming soon)

Microsoft's new unified cloud analytics platform.

Azure's vast array of data service can be overwhelming, individually they are compelling but choosing the right services and integrating them has always been the difficult part.

Azure Synapse reduces this friction by bringing together the best of Azure's existing data services along with some powerful new features and making them play together nicely. Services that you know and love include Azure Data Factory, Mapping Data Flows, Power BI and of course SQL Pools (formally SQL Data Warehouse).

What this means is that it's now possible to explore data, run experiments, develop pipelines and operationalize solutions from a single intuitive web-based UI. While it's still early days it is starting to feel like these services were finally designed to work together and we think this will become more so as the product matures.

WE are particularly excited about the new SQL Serverless option which allows you to query data stored in your storage account or data lake without the need to spin up any clusters or compute resource. You simply point your query at your data and you are charged based on the amount of data you read. What's more, almost any existing tooling that supports SQL Server will just work.

The all new Spark environment is a breeze to setup, security and sign-on is seamless and connecting to storage accounts is very straight forward. It comes with an nteract based notebook experience for documenting your experiments which feels intuative and modern. It also comes with a .NET Kernel courtesy of the excellent .Net Interactive.

Another very interesting feature is the integration with Cosmos DB. You can now perform powerful analytical queries over your application data from Azure Synapse within minutes of it arriving in your Cosmos DB collection. Setting it up is simple and once up and running, you can run analytical queries using SQL Serverless or Spark, you can even join and combine data with other data you have in your data lake.

We also love that Power BI is part of the Synapse story, bringing all the best bits of Power BI to data engineers and professionals.

Read our blog posts about Azure Synapse Analytics

How to access multi-select choice column choice labels from Azure Synapse Link for Dataverse with PySpark or SQL

How to access multi-select choice column choice labels from Azure Synapse Link for Dataverse with PySpark or SQL

Jessica Hill

Learn how to access multi-select choice column choice labels from Azure Synapse Link for Dataverse using PySpark or SQL.
Introduction to Python Logging in Synapse Notebooks

Introduction to Python Logging in Synapse Notebooks

Jonathan George

The first step on the road to implementing observability in your Python notebooks is basic logging. In this post, we look at how you can use Python's built in logging inside a Synapse notebook.
SQLBits 2024 Workshop - DataOps: How to Deliver Data Faster and Better with Microsoft Cloud

SQLBits 2024 Workshop - DataOps: How to Deliver Data Faster and Better with Microsoft Cloud

Ed Freeman

Explore the practical methods of implementing a DataOps-driven modern data platform in the Microsoft Cloud, mastering the art of delivering high-quality data products.