Hello!
In this blog we are going to learn Data services of azure. Consider this as one of the most important topic for exam.
1. Azure SQL
It is a relational database, based on Microsoft SQL server.
1.1 Azure SQL DB - Paas DB hosted in Azure
1.2 Azure SQL managed instance - Hosted instance of SQL server
1.3 Azure SQL VM - VM with SQL installed
DBA used Azure SQL DB for supporting Line of Business Application which uses transactional data.
Data Engineer uses it for data pipeline to perform ETL.
Data analyst use it for creating reports.
2. Azure Database for open source relational Database
2.1 Azure Database for MySQL - Open source database for used in Linux, Apache, MySQL, and PHP (LAMP) stack apps.
2.2 Azure Database for MariaDB - MariaDB offers compatibility with Oracle Database
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2.3 Azure Database for PostgreSQL - a **hybrid relational-object database. You can store data in relational tables, but a PostgreSQL database also enables you to store custom data types, with their own non-relational properties.
It is used by DBA to support transactional applications.
3. Azure CosmosDB
NoSQL DB, it supports multiple APIs, store and manage data as JSON
Cosmos DB instances may be provisioned and managed by a database administrator
Data engineers often need to integrate Cosmos DB data sources into enterprise analytical solutions that support modeling.
Reporting by data analysts.
4. Azure Storage
It allows to store data in
Blob containers - These are cost effective, stores files in binary
File share - Network file share
Tables - key-value storage
Data engineers use this to host data lakes
5. Azure data factory
It defines and schedule data pipeline to transform data by data engineers for ETL.
6. Azure Synapse Analytics
It is a data analyst solution, provides single service interface for multiple analytical capability includes :
Pipelines - based on the same technology as Azure Data Factory.
SQL - a highly scalable SQL database engine
Apache Spark - an open-source distributed data processing system that supports multiple programming languages and APIs, including Java, Scala, Python, and SQL.
Azure Synapse Data Explorer - a high-performance data analytics solution that is optimized for real-time querying of log and telemetry data using Kusto Query Language (KQL).
Data analysts and data engineers use this
7. Azure Databricks
Combines the Apache Spark data processing platform with SQL database semantics and an integrated management interface to enable large-scale data analytics.
8. Azure HDInsights
Azure-hosted clusters for popular Apache open-source big data processing technologies, including:
Apache Spark - Data processing system
Apache Hadoop - uses MapReduce, for large volumes of data
Apache Hbase - Open source for large scale NoSQL DB
Apache Kafka - message broker for data stream processing.
9. Azure stream analytics
Real time stream processing engine that captures stream of data from an input and writes result to output.
Data engineers can incorporate Azure Stream Analytics into data analytics architectures that capture streaming data for ingestion into an analytical data store or for real-time visualization.
10. Azure data explorer
High performance querying of data.
Data Analysts can use this for IoT, telementery data.
11. MS Purview
It creates map of your data and track lineage across multiple data source and systems.
12. MS Power BI
Analytical data modelling and report that data analyst can create.
Thank for reading :)
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