Evolution of Azure SQL Data Warehouse...
Azure Synapse Analytics is a de-facto service for combining data warehousing and big data analytics, with many more new features. Synapse Analytics fits in the overall data landscape where Azure Data Lake Storage forms the bedrock of big data storage, Power BI forms the visualization layer and Synapse Analytics for analysis of data stored in Data Lake.
Azure Synapse Analytics is an unlimited information analysis service aimed at large companies that was presented as the evolution of Azure SQL Data Warehouse, bringing together business data storage and macro or Big Data analysis.
Synapse provides a single service for all workloads when processing, managing and serving data for immediate BI and data prediction needs. The latter is made possible by its integration with Power BI and Azure ML. It provides the freedom to handle and query huge amounts of information either on demand serverless for data exploration and ad hoc analysis, or with provisioned resources, at scale.
Microsoft’s offers it as SaaS with below features:
- SQL Analytics/Cluster (pay per unit of computation & TB processed, on demand basis with impact on cost savings)
- Apache Spark fully integrated
- Connectors with multiple data sources
It uses Azure Data Lake Storage Gen2 as a data warehouse and a consistent data model that incorporates administration, monitoring and metadata management sections.
Everything is encompassed within the Synapse Analytics Studio that makes it easy to integrate AI, ML, IoT, intelligent applications or BI, all within the same unified platform.
Different layers of Azure Synapse Analytics platform is depicted below:
Core features of Synapse Analytics:
- Synapse Analytics Studio is a web-based IDE to enable code-free or low-code developer experience to work with Synapse Analytics.
- Synapse supports a number of languages like SQL, Python, .NET, Java, Scala, and R that are typically used by analytic workloads.
- Synapse Analytics is basically an analytics service that has a virtually unlimited scale to support analytics workloads.
- Data Lake Storage is suited for big data scale of data volumes that are modeled in a data lake model. This storage layer acts as the data source layer for Synapse. Data is typically populated in Synapse from Data Lake Storage for various analytical purposes.
- Synapse is integrated with numerous Azure data services as well, for example, Azure Data Catalog, Azure Lake Storage, Azure DataBricks, Azure HDInsight, Azure Machine Learning, and Power BI.
- Synapse supports two types of analytics runtimes – SQL and Spark (in preview as of Sept 2020) based that can process data in a batch, streaming, and interactive manner.
- Synapse also provides integrated management, security, and monitoring related services to support monitoring and operations on the data and services supported by Synapse.
- Synapse Workspaces (in preview as of Sept 2020) provides an integrated console to administer and operate different components and services of Azure Synapse Analytics.