1. Big Data Processing
1.1. Azure HDInsight
1.1.1. A cloud-based service that makes it easy to process big data using popular open-source frameworks.
1.1.1.1. Apache Spark: A unified analytics engine for large-scale data processing.
1.1.1.2. Apache Hadoop: A framework for distributed storage and processing of large data sets.
1.1.1.3. Apache HBase: A scalable, distributed database that supports structured data storage.
1.1.1.4. Apache Kafka: A distributed streaming platform for building real-time data pipelines and streaming applications.
1.2. Azure Databricks
1.2.1. An Apache Spark-based analytics platform optimized for Azure.
1.2.1.1. Provides collaborative notebooks for data engineering, data science, and machine learning.
2. Real-Time Processing
2.1. Azure Stream Analytics
2.1.1. A real-time analytics service that can ingest and analyze streaming data from multiple sources simultaneously.
3. Data Governance and Management
3.1. Microsoft Purview
3.1.1. A data governance and compliance service to manage and secure data across various sources, ensuring compliance and data lineage.
3.2. Microsoft Fabric
3.2.1. Although primarily for analytics and data integration, it also plays a role in data governance and management through its integrated approach, providing a unified platform for managing data across the organization.
4. Relational Databases
4.1. Azure SQL
4.1.1. A managed relational database service with SQL Server capabilities.
4.1.1.1. Azure SQL Database: A fully managed relational database service built for the cloud, with built-in high availability, backups, and scaling.
4.1.1.2. Azure SQL Managed Instance: Combines the best features of SQL Server with the operational and financial benefits of an intelligent, fully managed service.
4.1.1.3. Azure SQL VM: SQL Server on virtual machines, offering full control over the SQL Server instance and underlying operating system.
5. Non-Relational Databases
5.1. Azure Cosmos DB
5.1.1. A globally distributed, multi-model database service.
5.1.1.1. JSON documents: Schema-free data model for flexible and scalable document storage.
5.1.1.2. Key-value pairs: Simple, highly performant data storage for key-value data.
5.1.1.3. Column-families: A NoSQL store that uses tables and columns for storing data, similar to HBase.
5.1.1.4. Graphs: Support for graph databases with Gremlin API for complex relationships and queries.
5.2. Azure Database for open-source relational databases
5.2.1. This includes services like Azure Database for MySQL, PostgreSQL, and MariaDB.
5.2.1.1. Azure Database for MySQL: A managed database service for app development and deployment using MySQL.
5.2.1.2. Azure Database for MariaDB: A managed MariaDB service for app development and deployment.
5.2.1.3. Azure Database for PostgreSQL: A managed PostgreSQL database service for app development and deployment.
6. Storage Solutions
6.1. Azure Storage
6.1.1. Includes Blob Storage, Disk Storage, File Storage, and Queue Storage.
6.1.1.1. Blob containers: Scalable object storage for unstructured data such as text and binary data.
6.1.1.2. File shares: Fully managed file shares in the cloud, accessible via SMB protocol.
6.1.1.3. Tables: A NoSQL store for structured data, offering a schemaless design for rapid development.
7. Data Integration and ETL
7.1. Azure Data Factory
7.1.1. A data integration service that orchestrates and automates the movement and transformation of data.
7.2. Pipelines in Azure Synapse Analytics
7.2.1. Allows for the integration and orchestration of data flows within Synapse, supporting complex ETL processes.
8. Analytics
8.1. Azure Synapse Analytics
8.1.1. A unified analytics service that combines big data and data warehousing.
8.1.1.1. SQL: Offers data warehousing capabilities with SQL-based querying.
8.1.1.2. Apache Spark: Integrated big data analytics for large-scale data processing.
8.1.1.3. Azure Synapse Data Explorer: Optimized for fast, interactive analytics over large volumes of data.
8.2. Azure Data Explorer
8.2.1. A fast and highly scalable data exploration service.
8.2.1.1. For log and telemetry data analysis.