The demand for real-time data is stronger than ever. Timely access to data can make or break the decision-making of businesses. Until recently, having access to real-time data involved complex and expensive data pipelines.

While organisations have traditionally used batch or micro-batch loading for their data, Snowflake just flipped the script on real-time data ingestion with the introduction of Snowpipe Streaming. In this post, you will learn about Snowpipe Streaming, explore its capabilities, and advantages.

What is Snowpipe Streaming

Snowflake’s data ingestion services have long been the backbone of efficient loading into Snowflake data warehouses.

Snowpipe is a micro-batch, serverless data ingestion service designed to simplify the process of loading data into Snowflake data warehouses. Snowpipe streamlines the process of transferring data from source to destination by automatically building pipelines once new files are ingested.

However, it’s important to note that Snowpipe, while continuous, falls short of being truly real-time. Users may experience a delay of several minutes before the ingested data becomes available for querying. In cases where a large volume of data is pushed through Snowpipe simultaneously, this may lead to throughput issues where writes queue up.

Snowpipe Streaming is a new data ingestion feature from Snowflake. Powered by a Java-based open-source API, it is designed for high-throughput and low-latency streaming data ingestion.

Unlike its predecessor, It enables users to write rowsets directly into Snowflake tables, eliminating the need for setting up complex pipeline or intermediary cloud storage like Amazon S3.

Snowpipe Streaming serves as an ingestion method for the Snowflake Connector for Kafka. This seamless integration enables the direct ingestion of streaming data from Kafka topics into Snowflake tables, combining the power and scalability of these two technologies.

Let’s explore this further.

Snowpipe Streaming: The Simple Path from Kafka to Snowflake

Snowpipe Streaming is the ideal conduit for connecting Kafka and Snowflake, offering real advantages that go beyond the technical complexities.

This dynamic solution ensures data reaches Snowflake nearly as soon as it’s generated, providing users with the critical advantage of making decisions with the freshest data.

Not only does Snowpipe Streaming deliver speed, but it’s also highly efficient, optimising data loading and reducing the strain on Snowflake’s infrastructure, ultimately resulting in cost savings. Say goodbye to complex data pipelines and complex setups because Snowpipe Streaming handles the heavy lifting, allowing end-users to focus on leveraging their data for informed decision-making and business growth.

Building on the advantages of Snowpipe Streaming as the conduit from Kafka to Snowflake, the business rationale is clear. This streamlined integration ensures rapid data access, enabling timely decisions. It optimises efficiency, cutting operational costs and eliminating complexity in data flow.

Now, Enter Digazu

While Snowpipe Streaming establishes an efficient pathway for data to flow from Kafka to Snowflake, Digazu ensures that the data that transitions from the different sources to Kafka is readily transformed and available to use for real-time projects.

Here’s why it’s a business-wise choice:

Unified data access: Digazu breaks down data silos and enables you to seamlessly combine data from various sources, including databases, files, and cloud services. This means you’re not just streamlining real-time data from one source; you’re unifying all your data into streams. By facilitating the combination of data across silos, Digazu fosters collaboration, ensures the free flow of data throughout your organisation and maximises the value of your data assets.

Readily transformed data: One of Digazu’s standout features is its real-time transformation capabilities, made possible through the use of Flink. In fact, Digazu enables users to transform data before it moves to Snowflake. Some of these transformations include enriching and combining data in real-time.

Additionally, Digazu’s low-code approach ensures that you can tackle even the most complex data transformation processes with ease.

By adopting Digazu, some of the benefits that you can reap comprise:

Expanding real-time projects: Thanks to Digazu, you can expand the scope of your real-time projects, with access to a more extensive pool of real-time data. This means tapping into a broader array of information sources, gaining deeper insights, and making more informed decisions in real-time. With this increased data availability, businesses can have access to a wider range of use cases, such as predictive analytics, real-time monitoring or even fraud detection.

Improved governance: This encompasses aspects like risk reduction, anonymization, and the retention of only essential data. By implementing these governance measures, organisations can minimise potential risks associated with data handling, ensure compliance with data protection regulations, and efficiently manage data by retaining only what is truly valuable and relevant.

Costs reduction: Achieving cost efficiency is another critical benefit. Conducting data transformations upstream, before it is stored or processed, is a more efficient approach. This process not only reduces the volume of data that needs to be managed but also cuts down the expenses of data storage and processing. This way, organisations can make significant savings while maintaining effective data management practices.

The Power of the Duo

Together, Snowpipe Streaming and Digazu provide a straightforward path to real-time data integration. Snowpipe Streaming is your high-speed data highway from Kafka to Snowflake. Digazu is your on-ramp, making sure all your data, no matter where it comes from, can smoothly flow on that highway.

In a nutshell, why use Digazu and Snowpipe Streaming? It’s simple:

Together, Snowpipe Streaming and Digazu create an end-to-end solution for real-time data integration to Snowflake, characterised by cost-efficiency, streamlined operations, and reduced risks. Snowpipe Streaming ensures you get the freshest data from Kafka to Snowflake quickly and efficiently while Digazu brings together all your siloed data into the streams that you really need.

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