By: Christeena Uzhuthuval, PolarSled Product Lead, Snowflake Centre of Excellence, LTIMindtree

Ever tried to cook a gourmet meal with nothing but rice, salt, and oil? The result is something edible, even filling, but it lacks the flavor, color, and complexity that spices, herbs, and fresh produce bring. Similarly, AI can operate with basic, siloed datasets, but without diverse and enriched data sources, its insights remain bland and one-dimensional.

Data silos—isolated stores locked into different systems, formats, or owners—hide the bigger picture. Finance can’t see marketing trends; operations miss shifts in customer sentiment; product teams lose sight of supply‑chain constraints. AI needs these cross‑domain signals to spot correlations, detect anomalies, and surface opportunities a single data source can’t reveal. Put simply, the more complete the view, the more actionable the insight.

Where Openflow enters the kitchen

Snowflake’s acquisition of Datavolo introduced Openflow—a fully managed, scalable data‑integration layer embedded in the Snowflake Data Cloud. Built on the proven foundation of Apache NiFi, Openflow acts as the central nervous system for data movement and transformation, turning scattered information into a ready‑to‑use resource for any AI or analytics initiative.

By orchestrating pipelines across databases, SaaS apps, cloud storage, and unstructured media, Openflow becomes the pillar of an AI‑ready lakehouse. It democratizes access, enforces governance, and eliminates the engineering complexity typically required to prevent data silos.

This article aims to provide an overview of Snowflake Openflow, what makes it unique, and why it matters for AI‑driven organizations.

The DNA of Openflow

Openflow is based on Datavolo, a dataflow infrastructure purpose-built for complex observability needs and training large language models (LLMs). It delivers data in formats best consumable by modern AI system . One prominent example is Retrieval Augmented Generation (RAG), which depends on the data being parsed, chunked, and vectorized to be appropriately used by AI models.

Datavolo’s founders originally created Apache NiFi to help enterprises capture, transform, and distribute data at scale. They later launched Datavolo to support multimodal data ingestion, including text, images, and audio for advanced AI workflows. Recognizing the strategic fit, Snowflake acquired Datavolo. With this acquisition, Snowflake now has its own native data integration service—Openflow—tightly embedded within the Snowflake Data Cloud. (fig. 1)

Figure 1: Relationship between Openflow, Datavolo and Apache NiFi (Envisioned State)

How Snowflake capitalizes NiFi’s potential

Openflow leverages NiFi’s core strengths in data collection, routing, transformation, and distribution, ensuring robust performance for demanding data pipelines. It simplifies pipeline creation and management, effortlessly handling varying data volumes with Snowflake’s elasticity. Users can visually design and orchestrate ETL/ELT data pipelines without the burden of infrastructure management.

Additionally, Openflow provides a rich library of pre-built connectors and extensible processors for diverse data manipulation tasks. Being native to the Snowflake Data Cloud ensures tight integration with its security, governance, and data sharing features. This aids the data movement within the Snowflake environment to be streamlined, thereby reducing complexity and enhancing data flow.

Openflow is a key component of Snowflake’s unified data platform vision, complementing data warehousing, data lake, and data science functionalities. It empowers users to efficiently bring data from various sources, prepare it for analysis, and drive data-driven initiatives within a governed and performant environment, by Apache NiFi.

Furthermore, NiFi’s valuable data provenance features, tracking data lineage and history, are accessible within Openflow for enhanced data governance and debugging. In short, Openflow provides the power and flexibility of the established Apache NiFi engine, offering a robust and user-friendly data integration experience. You gain NiFi’s strengths without the operational burden of managing it independently. Openflow inherits NiFi’s extensive ecosystem of connectors, providing seamless connectivity to a vast array of data sources and destinations.

Nurturing the AI vision

Remember when building an AI pipeline meant weeks of scripting, debugging, and hoping your code would survive the next product update? What if creating that same pipeline felt more like arranging building blocks than writing complex prose?

Traditionally, integrating data for AI demanded custom-built pipelines, heavy coding, and niche expertise. These requirements became bottlenecks, shutting out analysts, citizen data scientists, and even some seasoned engineers. Openflow shifts this paradigm toward a more modern, AI-ready architecture. Its drag‑and‑drop canvas and expansive library of pre‑built connectors let data engineers and data scientists design sophisticated pipelines—no marathon coding sessions required. The result? A lower barrier to entry and broader participation in AI projects across the organization.

Connectivity is another game‑changer. Openflow’s broad connectivity seamlessly integrates diverse AI data sources outside Snowflake, including databases, cloud storage, SaaS applications, and the increasingly critical world of unstructured and multimodal data—text, images, audio, and video. It acts as a universal translator, harmonizing data regardless of origin or format so AI models can consume it without friction. As your initiatives expand, Snowflake’s elasticity and Apache NiFi’s underlying architecture allow Openflow to scale effortlessly—no painful re‑engineering needed.

But pipeline creation is only half the story. Openflow’s visual interface enables users to clean, enrich, and prepare data for AI algorithms right on the canvas. Why ship data to a separate environment when you can transform it in place? Faster iterations follow: data scientists’ experiment, analysts add domain nuances, and the organization collectively benefits from models trained on unified, high‑quality information.

Security and governance travel with data. Openflow inherits Snowflake’s robust compliance framework, while built‑in provenance tracks every transformation for reproducibility and auditability—essentials for regulated industries. It integrates seamlessly with Snowpark, and other Snowflake AI/ML tools, supports real‑time data streams for low‑latency applications, and runs on Snowflake’s consumption‑based pricing. By eliminating infrastructure headaches, Openflow speeds time‑to‑value, encourages collaboration, and delivers cleaner data for faster AI deployment. How much innovation could your team unlock if infrastructure became invisible?

Openflow availability

Openflow is now generally available on Snowflake for AWS‑hosted accounts, with deployments in either a managed VPC or a bring‑your‑own VPC. Current setup involves standard AWS components, EC2 instances, load balancers, IAM roles, and EKS clusters. But Snowflake plans to automate this via an SPCS container service, promising a smoother, self‑service experience.

Conclusion

Snowflake’s acquisition of Datavolo reflects a shared vision: simplify multimodal and scalable data pipelines for AI. By building Openflow on Apache NiFi, Snowflake has transformed Datavolo’s core promise into a native feature of the Data Cloud. As reliance on AI grows, Openflow streamlines data preparation, accelerates model deployment, and redefines how information fuels intelligent applications.

By simplifying pipeline creation, handling diverse data, and providing a scalable and governed environment, Openflow empowers organizations to overcome data silos and unlock the full potential of their information. This, in turn, helps in driving intelligent applications and gaining a competitive edge in the AI era. Whether you are ingesting structured logs, unstructured text, programmatic, and sensor data, or rich media, Openflow positions you to tackle today’s toughest business challenges. The future of AI innovation depends on accessible, well‑integrated data—are you ready to tap in?

References

1. Snowflake Openflow Documentation: https://docs.snowflake.com/en/user-guide/data-integration/openflow/about
2. Snowflake Openflow: https://www.snowflake.com/en/product/features/openflow/