The world is expected to create 181 zettabytes of data this year — an astonishing figure that just goes to show that creating data is easy. Making it useful, however, is an entirely different story.

For many businesses, that starts with data integration — bringing together information from various sources to coexist and cooperate under a shared framework. It sounds simple, but in practical terms, data integration has become quite complex, often requiring engineers to build and maintain intricate pipelines that often sprawl across numerous platforms and multiple tools. Particularly, data engineering teams are often faced with the impossible trade-off between simplicity and control. If they need highly controllable integration pipelines, they face complexity that demands significant infrastructure management. However, “simplified” solutions are often hidden in a black box, making it impossible to trace data journeys, identify quality issues and understand the data, thereby sacrificing transparency and customization. Today, most customers solve this conundrum by prioritizing one over the other, which could ultimately contribute to higher costs with a complex tech stack and potentially risk-prone pipelines. 

Snowflake Openflow, though, is designed to change all that by bringing data flows right to data’s doorstep, making data movement as simple as it should be without forgoing flexibility and control. With two powerful deployment options — a customer-hosted option through bring your own cloud (BYOC) or a Snowflake hosted option through Snowpark Container Services (SPCS), for a fully integrated experience — Openflow can address the needs of any enterprise architecture. 

To understand which deployment is right for your organization, it’s important to understand the benefits and use cases best served by each. Having covered the BYOC deployment in a previous post, we will now shine light on the new Snowflake hosted option with SPCS, now available in preview in AWS and Azure. This option offers a simple, zero-ops way to run data flows with the Snowflake AI Data Cloud. 

Data movement with zero ops: Introducing Openflow Snowflake Deployments, a Snowflake hosted option

From rapid provisioning to seamless interoperability with Snowflake features, such as Streamlit or Snowflake Intelligence, Openflow Snowflake Deployments is the proverbial easy button — a plug-and-play option that connects data from any source to any destination within minutes and with minimal complexity. For seasoned data engineers, it removes superfluous operational burdens, while empowering them with the power of limitless extensibility and adaptability. For business analysts and data scientists, it puts the power of end-to-end data engineering within reach.

With this zero-ops option, Snowflake manages all of the infrastructure — no extra cloud accounts to provision — with streamlined security and networking configuration. Provisioning a runtime in Openflow is as simple as running any other data pipeline feature in a Snowflake warehouse, making data integration and movement effortless. In this managed, SaaS-like experience, Snowflake handles patching, security and scaling of the containerized service seamlessly within any account, ultimately presenting users with a quicker, more direct path to value. 

Use cases for Openflow Snowflake Deployments

To help realize Snowflake’s vision of end-to-end data engineering on a single platform, Openflow Snowflake Deployments plays an integral role in five key areas:

• Incorporating full-fidelity data in the bronze layer: Landing raw data from various sources directly into Snowflake and using Openflow Snowflake Deployments to extract and load 

• Enriching data: Running pipelines to enrich tables that already exist inside Snowflake

• Going from ingest to insight in one place: Building applications where the entire data lifecycle (ingest, process and serve) happens within the Snowflake ecosystem 

• Transforming raw data to insights with AI: Ingesting unstructured data and then, for instance, using Snowflake Intelligence to search and understand it better, all in concert with users’ other structured data

• Employing reverse ETL: Closing the loop on insight generation by sharing with external operational systems via APIs, messaging infrastructure, etc.

Key benefits

At the core of the Openflow option with SPCS is an unmatched simplicity that Snowflake users have come to love and expect; it simply works. There’s no need to manage infrastructure, configure networking or worry about security boundaries between systems. It frees users to focus on realizing value from their data rather than constantly looking at the plumbing. 

Leveraging Snowflake’s familiar, robust security features and role-based access control (RBAC) model, Openflow Snowflake Deployments also allows users to maintain consistent governance controls across an entire data ecosystem. And since compute is co-located with data in Snowflake, the SPCS deployment helps minimize data transfer latency and egress fees between the cloud provider and Snowflake. Ideal for transformations on data already in Snowflake, Openflow Snowflake Deployments results in overall faster processing times and more efficient resource utilization, key for cost-optimization efforts.

Moreover, a single, consolidated Snowflake bill all but eliminates the tedious task of tracking expenses across multiple platforms and generally simplifies procurement and financial management. Having everything on one bill makes it easier to understand usage and expenses, as companies look to optimize the total cost of ownership for their data infrastructure.

Taking the right path to bring data where it matters

The choice between Openflow BYOC and Openflow Snowflake Deployments isn’t a matter of which is “better” but rather which deployment is right for the specific needs and architecture of the job. 

To help guide your organization’s decision, consider this simple framework, noting that many organizations use both options for different scenarios:

• Does your data pipeline interact heavily with systems in your own VPC or on-premises environment? If so, start with BYOC to maintain tight integration with your existing infrastructure.

  • Preprocessing sensitive data: Some customers have mandates to redact sensitive data such as PII before writing to destination systems. This is easily accomplished with Openflow BYOC.

  • Networking flexibility: More complex networking topologies are best aligned with the BYOC deployment.

• Is your pipeline’s primary destination or source Snowflake, and do you value operational simplicity above all? In this case, Openflow Snowflake Deployments is likely the optimal choice, offering a seamless, zero-ops experience fully integrated with your Snowflake environment.

  • Reverse ETL scenarios: Extracting data from Snowflake as a source and writing it to a different target is best aligned with SPCS deployments.

  • Private connectivity for simple topologies: Snowflake offers outbound private connectivity for SPCS, for Business Critical Edition customers.

The best part? Deployment and runtime options are set at the pipeline level, meaning for different data sources and connectivity requirements, you can benefit from both BYOC and Openflow Snowflake Deployment options. Openflow simplifies data integration, meeting you where your data lives and providing the tools you need to transform it into actionable insights.

To learn more about both deployment options, visit the Snowflake Openflow documentation or contact us. We invite you to discover how it can transform your data integration strategy today.