Modern data engineering relies on real-time analytics as a vital component. This capability empowers businesses to extract insights from data as it is generated in near real-time. To support this, the Azure Data Platform offers a variety of services, such as Azure Stream Analytics, Azure Data Explorer, Azure Data Factory using CDC, and Azure Synapse Structured Streaming Notebook. This article will explore each of these options and describe their distinct potential uses.
What are the top Azure Data Platform Services?
Here are the top Azure Data Platform Services for Real-Time Insights
- Azure Stream Analytics
- Azure Data Explorer
- Azure Data Factory using CDC
- Azure Synapse Structured Streaming Notebook
Azure Stream Analytics:
Azure Stream Analytics is a fully managed service that processes streaming data in near real-time, with the ability to handle high volumes of data and provide low latency processing. It supports various inputs, including Azure Event Hubs, Azure IoT Hub, Azure Blob Storage, and Azure Data Lake Gen 2. Stream Analytics also supports a range of outputs, including Azure Blob Storage, Azure SQL Database, Azure Cosmos DB, Power BI, and Azure functions. This service is ideal for real-time data transfer and is often used for log analysis, real-time monitoring, and IoT applications.
Azure Data Explorer:
Another useful service provided by Azure Data Platform is Azure Data Explorer. It is designed to analyse and process large volumes of data in near to real-time, allowing complex ingestion over large data sets with low latency. Data Explorer supports inputs from various sources, including Event Hubs and Blob Storage using Event Grids. This service is commonly used for log analysis, IoT applications, and time-series analysis.
Azure Data Factory using CDC:
For capturing micro-batch changes made to data sources in near real-time latency and applying them to a target database, Azure Data Factory (CDC) is an excellent service. It supports various data sources, including SAP CDC, SQL Server, Azure SQL Managed Instances, and Cosmos DB, among others. Data Factory (CDC) is an ideal option for data replication, landing, and backup purposes.
Azure Synapse Structured Streaming Notebook:
Lastly, Azure Synapse Structured Streaming Notebook is a collaborative web-based notebook that allows for near real-time data analysis and visualization of streaming data. The service provides low latency processing and supports inputs from Azure Event Hubs, Azure IoT Hub, and Azure Data Lake Gen 2.It’s ideal for performing real-time data analysis and visualization. It is commonly used for real-time monitoring, anomaly detection, and predictive analytics.
Real-time processing architecture with potential components:
A real-time processing architecture consists of real-time message ingestion, stream processing, an analytical data store, and analysis and reporting. One of the biggest challenges of real-time processing solutions is to ingest, process, and store messages in real-time, especially at high volumes, without blocking the ingestion pipeline. The data store must support high-volume writes, and the solution must be able to act on the data quickly. In Azure, the recommended technologies for real-time processing solutions include Azure Event Hubs, Azure IoT Hub, Apache Kafka for real-time ingestion, and Azure Storage Blob Containers or Azure Data Lake Store for data storage.
Azure provides different options for stream processing, such as Azure Stream Analytics and Spark Streaming, Azure Data explorer which allow you to run perpetual queries against an unbounded stream of data. Both support temporal and geospatial constructs and can be extended using SQL-based query language or Spark language, respectively.
Optimal Real-Time Analytics: What Makes This Processing Architecture Stand Out?
It is important to note that while this real-time processing architecture is effective, this one is only one of many possible approaches to real-time analytics and may be the best fit for some or many business needs.
(Processed data can be used for historical reporting and analysis in the same way as batch processed data using azure synapse analytics as analytical data store, and Power BI can be used to publish real-time reports and visualizations.)
What Are the Key Benefits of Leveraging Azure Synapse Analytics and Power BI?
By leveraging the capabilities of Azure Synapse Analytics and Power BI, organizations can gain valuable insights from their near real-time data. Stream processing provides low latency processing and allows you to visualize and explore your data in real-time. Power BI enables you to create interactive reports and dashboards to display the processed data.