This post helps you understand what SQL streaming is, when and why to use it, and discusses some key factors to consider when choosing the right streaming database.
In today’s world of real-time data processing and analytics, streaming databases have become an essential tool for businesses that want to stay ahead of the game. These databases are specifically designed to handle data that is generated continuously and at high volumes, making them perfect for use cases such as the Internet of Things (IoT), financial trading, and social media analytics. However, with so many options available in the market, choosing the right streaming database can be a daunting task.
This post helps you understand what SQL streaming is, the streaming database, when and why to use it, and discusses some key factors that you should consider when choosing the right streaming database for your business.Learning Objectives
You will learn the following throughout the article:
What streaming data is (event stream processing)
What is the Streaming SQL method?
Streaming Database features and use cases
Top 5 streaming databases (both open-source and SaaS).
Criteria for choosing a streaming database
Let’s review quickly some concepts like what’s streaming data, streaming SQL, and databases in the next few sections.What Is Streaming Data?
A stream is a sequence of events/data elements made available over time. Data streaming is a method of processing and analyzing data in real-time as it’s generated by various sources such as sensors, e-commerce purchases, web and mobile applications, social networks, and many more. It involves the continuous and persistent collection, processing, and delivery of data in the form of events or messages.
You can ingest data from different data sources such as message brokers Kafka, Redpanda, Kinesis, Pulsar, or databases MySQL or PostgreSQL using their Change Data Capture (CDC), which is the process of identifying and capturing data changes.What Is Streaming SQL?
Once you collect data, you can store this data in a streaming database (in the next section, it is explained), where it can be processed and analyzed using SQL queries with SQL streaming. It is a technique for processing real-time data streams using SQL queries. It allows businesses to use the same SQL language they use for batch processing to query and process data streams in real-time.
The data can be transformed, filtered, and aggregated in real-time from the stream into more useful outputs like materialized view (CREATE MATERIALIZED VIEW) to provide insights and enable automated decision-making. Materialized views are typically used in situations where a complex query needs to be executed frequently or where the query result takes a long time to compute. By precomputing the result and storing it in a materialized view (virtual tables), queries can be executed more quickly and with less overhead. PostgreSQL, Microsoft SQL Server, RisingWave or Materialize support materialized views with automatic updates.
