Azure Synapse Analytics is an unlimited information analysis service aimed at large companies that was presented as the evolution of Azure SQL Data Warehouse (SQL DW), 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 business intelligence and data prediction needs. The latter is made possible by its integration with Power BI and Azure Machine Learning, due to Synapse’s ability to integrate mathematical machine learning models using the ONNX format.
Azure Data Lake Analytics Data Lake Analytics is an on-demand analytics job service. It is optimized for distributed processing of very large data sets stored in Azure Data Lake Store
HDInsight is a managed Hadoop service. Use it deploy and manage Hadoop clusters in Azure. For batch processing, you can use Spark, Hive, Hive LLAP, MapReduce.
Azure Databricks is an Apache Spark-based analytics platform. You can think of it as “Spark as a service.” It’s the easiest way to use Spark on the Azure platform.
Microsoft’s service is a SaaS (Software as a Service), and can be used on demand to run only when needed (which has an impact on cost savings).
It has four components:
- SQL Analytics with full T-SQL based analysis: SQL Cluster (pay per unit of computation) and SQL on demand (pay per TB processed).
- Apache Spark fully integrated.
- Connectors with multiple data sources
Azure Blob storage is Microsoft’s object storage solution for the cloud. Blob storage is optimized for storing massive amounts of unstructured data. Unstructured data is data that doesn’t adhere to a particular data model or definition, such as text or binary data
Azure Storage redundancy — Azure Storage always stores multiple copies of your data so that it is protected from planned and unplanned events, including transient hardware failures, network or power outages, and massive natural disasters.
Access tiers for Azure Blob Storage — hot, cool, and archive. Azure storage offers different access tiers, allowing you to store blob object data in the most cost-effective manner. Available access tiers include:
- Hot — Optimized for storing data that is accessed frequently.
- Cool — Optimized for storing data that is infrequently accessed and stored for at least 30 days.
- Archive — Optimized for storing data that is rarely accessed and stored for at least 180 days with flexible latency requirements, on the order of hours.
For complete notes visit : AZ 900
Originally published at https://www.yadsmic.com on March 29, 2021.