Choosing a data load strategy
Two of the key parameters you have to consider when you design your data load strategy are your tolerance for latency and the data volume that you will process.
In some scenarios, your business may require seeing the latest data available as soon as possible to enable quick decision-making, while in others you may be able to work with data from a day, or a few days ago, to perform analysis on historical data. Working with low latency in data ingestion implies inserting smaller chunks of data more frequently, while at a higher latency, you will insert larger volumes of data maybe once a day, or a few times per day.
To address these scenarios, Azure Synapse Data Explorer works with two ingestion strategies: streaming ingestion and batching ingestion. Let’s look at these strategies in detail.
Streaming ingestion
When real-time analytics is a hard business requirement, you will most likely implement a streaming ingestion strategy. This strategy...