Organizations face real challenges when it comes to moving and managing data. While the Snowflake AI Data Cloud provides robust storage and analytics, many teams still struggle with the complexities of ingesting data from various sources.
In this blog, we’ll break down the common hurdles in data ingestion and explain how Snowflake Openflow helps address them. You’ll learn how Openflow streamlines data extraction and movement, cutting down on manual work and minimizing disruptions.
We’ll also discuss how Snowflake, Openflow, and phData’s experience come together to offer a practical, scalable solution for managing data flows, improving governance, and maintaining efficiency.
Whether handling real-time or batch data, we’ll show how this powerful combination simplifies your data architecture and keeps things running smoothly.
Common Customer Pain Points in Data Ingestion
If you’re already using Snowflake, it’s fair to ask: why bring in a tool like Openflow? Isn’t Snowpipe already handling ingestion?
Snowpipe does a solid job loading data into Snowflake, but it doesn’t handle getting that data out of your source systems. That’s still your responsibility.
For most teams, that means building and maintaining custom pipelines—often brittle, hard to scale, and time-consuming to fix when they break (which can be as simple as a renamed column). These breaks slow down access to data, pull engineers away from higher-value work, and frustrate business users who are left waiting.
Even when things do work, these homegrown pipelines can be difficult to monitor, govern, or evolve. That’s where Openflow comes in: it’s built to simplify and stabilize moving data reliably from source to Snowflake with security, scale, and control.
What is Openflow (and Why Is It Different)?
Openflow separates orchestration and execution across a Control Plane and one or more Data Planes. The Control Plane, hosted as a Snowflake-managed service, lets you provision, manage, and monitor Data Planes.
The Data Plane executes pipelines using Apache NiFi-based Runtimes. It can run in your VPC (BYOC) or be fully managed in Snowflake, supporting multiple environments (e.g., dev, staging, prod), horizontal scaling, multi-node and multi-cluster deployments, and DR resilience.
Under the hood, Openflow leverages Apache NiFi, a trusted data movement framework, with native Snowflake integration for high performance, security, and governance. It offers an intuitive drag-and-drop interface and low-code dataflow design, making it accessible to both technical and non-technical users.
Rich metadata, lineage, and audit features provide full pipeline visibility and control across streaming, batch, and hybrid workloads. Runtimes are deployed via the Openflow CLI alongside the Data Plane Agent, which handles setup, component installation, and image sync from Snowflake’s System Image Registry. Authentication is managed via your OIDC provider, with custom DNS used to access the Runtime UI.
Why Snowflake + Openflow is a Big Deal
The combination of Snowflake and Openflow is a game changer for organizations looking to simplify and scale their data ingestion. With Openflow, teams get turnkey ingestion into Snowflake with minimal overhead—no more stitching together brittle, custom pipelines. Openflow’s real-time, event-driven architecture is built for modern use cases, enabling businesses to act on fresh data faster than ever.
Because Openflow runs within your environment and writes directly to Snowflake, you benefit from unified compute and storage, eliminating the need for separate ingestion infrastructure or redundant systems. Best of all, the integration is tightly aligned with Snowflake’s native security, governance, and cost management controls, ensuring that data movement is not only fast and efficient but also secure and compliant from end to end.
Why phData is Excited About Openflow
Snowflake’s acquisition of Openflow brings real advantages to customers looking to streamline data ingestion. It enables rapid prototyping with minimal setup, so teams can validate use cases early, without relying on heavy engineering. Built for real-time, event-driven pipelines, Openflow ensures critical data lands in Snowflake when it’s needed most.
Reusable pipeline templates reduce rework and speed up future integrations. Whether you’re bringing in ERP data, applying simple transformations, or supporting unstructured data for AI use cases, Openflow simplifies the process. Plus, it aligns with a Snowflake-first architecture—centralizing governance, reducing tool sprawl, and keeping costs under control.
While complex scenarios may still require some additional setup, Openflow’s flexibility and tight integration with Snowflake make it a strong fit for teams at any stage of their data journey.
The Power Trio: Snowflake + Openflow + phData
The combination of Snowflake, Openflow, and phData creates a seamless, scalable, and secure data ecosystem. With over a decade of expertise in data engineering, Snowflake, and automation, phData ensures that Openflow’s powerful ingestion capabilities are implemented with the right governance, scalability, and best practices.
Openflow simplifies data movement, while phData leverages its deep knowledge to optimize it for performance and compliance.
At the core, Snowflake remains the backbone—offering a unified platform for efficient data operations and real-time insights, all while keeping security and cost under control. Together, they provide a comprehensive solution for modern data needs.
Closing
Are you looking to improve your Snowflake ingestion pipeline? Want to understand how Openflow can enhance your data operations? phData is here to help.
With over a decade of experience working with Apache NiFi and Snowflake, we can guide you through the best practices for building scalable, automated data workflows.
Build a better data pipeline.
Contact our Snowflake team today to discuss your data ingestion needs, and let’s explore how we can optimize your data architecture for better performance, lower costs, and faster insights.
FAQs
How does Openflow differ from Snowpipe in terms of data ingestion?
While Snowpipe is excellent for loading data into Snowflake, it doesn’t handle extracting and moving data from your source systems. Openflow fills this gap by automating the entire ingestion process, from data extraction to delivery. With its native integration into Snowflake, Openflow streamlines data movement, allowing for faster, more reliable real-time data ingestion without the need for complex and fragile custom pipelines.
What does the architecture of Openflow look like, and how does it run in my environment?
Openflow is built on a modern, scalable architecture designed to run securely within your environment while offering tight integration with Snowflake. It comprises two main components: the Control Plane and the Data Plane.
The Control Plane is a managed service application within the Snowflake platform and accessible via the Snowsight UI. This centralized control ensures consistent management and orchestration across environments.
The Data Plane is where your pipelines actually run. Openflow pipelines are containerized and orchestrated using Apache NiFi. These pipelines can be deployed in two ways:
Bring Your Own Cloud (BYOC): Run in your own VPC for maximum control.
Fully managed in Snowflake: For simplified deployment and operations.
Multiple Data Planes can be connected to a single Control Plane to support different workloads or environments. Each Data Plane supports horizontal scaling, multi-node and multi-cluster deployments, and disaster recovery (DR) resilience.
A Data Plane Agent handles all the heavy lifting—setting up the environment, managing container image synchronization from Snowflake’s registry, and ensuring consistent and secure execution. This architecture puts you in control of authentication, DNS, and scaling, while keeping data movement fast, secure, and fully aligned with Snowflake’s operational model.
