Snowflake's newly released data ingestion service, Snowflake Openflow, represents a significant step for Snowflake users pursuing real-time data ingestion and AI-powered analytics. Built on Apache NiFi, Openflow targets modern, Snowflake-native use cases. However, it introduces limitations around deployment flexibility, connector availability, and cost transparency.
In contrast, CData Sync offers a mature, hybrid-ready data integration platform that supports diverse environments and predictable costs. In this post, we will discuss when to use each platform, highlighting ideal scenarios, technical differences, and strategic considerations to guide your decision.
What is Snowflake Openflow?
Snowflake Openflow extends the Snowflake platform by offering an all-in-one solution for data ingestion, storage, transformation, and AI-driven analytics. Designed for real-time data pipelines and built on Apache NiFi, Openflow enables preprocessing for Snowflake's native Cortex AI tools and is built for the modern data ecosystem. However, as a newly released product, Snowflake Openflow does have some current limitations, such as a limited connector library, and it is currently only available as an AWS bring-your-own-cloud (BYOC) deployment.
Key characteristics and differentiators:
- Built on Apache NiFi, a proven open-source data flow tool that allows data engineers to customize data flows and build custom connectors
- Requires hands-on development and orchestration to write and manage data flow logic, a step away from Snowflake’s typical low-code, managed service approach
- Native integration with Cortex AI tools for data preprocessing and "chat with your data" experiences
- Purpose-built for Snowflake and optimized for ingestion into Snowflake data warehouses
- Support for unstructured data sources, such as text, images, audio, sensor data, and video
What is CData Sync?
CData Sync is a universal data replication and integration platform that is built for the reliable movement of enterprise data across cloud, on-premises, and hybrid environments. It empowers organizations to build automated and scalable enterprise data pipelines all without writing any code, accelerating time-to-insight, while preserving architectural flexibility.
Key characteristics and differentiators:
- Provides universal connectivity, with over 250 enterprise connectors for databases, SaaS apps, cloud warehouses, and file systems.
- Predictable, connection-based pricing that is not based on data volume or usage frequency.
- Flexible deployment options such as on-premises, in the cloud (AWS or Azure), or through the hosted CData Sync Cloud service.
- Reverse ETL support, enabling data movement from databases and warehouses like Snowflake back into operational systems such as CRMs and ERPs.
- Support for In-Flight and Post-Flight transformations to apply filters, mappings, and SQL-based transforms before or after the data lands in the destination.
Key differences in architecture and deployment
The foundation of any ETL/ELT or data replication platform lies in its architecture and deployment flexibility. As organizations attempt to manage modern data ecosystems consisting of various data sources that span cloud, hybrid, and on-premises environments, the ability to adapt to different environments is strategically imperative.
Snowflake Openflow and CData Sync approach this challenge from fundamentally different angles. Openflow is built for Snowflake data ingestion, while Sync offers a more mature and diverse platform, designed for universal connectivity and implementation. Understanding the differences in how each tool is architected can help reveal tradeoffs in complexity, scalability, and long-term flexibility that fit your use case best.
Architecture
Snowflake Openflow is built on Apache NiFi, a powerful open-source programming framework, and is designed for real-time data streaming of unstructured data into Snowflake. While NiFi provides powerful customization and event-driven processing, it can also introduce added complexity. As a result, teams may need additional DevOps knowledge to configure processors, orchestrate data flows, and support custom connectors or transformations that often rely on custom scripting.
In contrast, CData Sync is built around standards-based connectivity, mainly JDBC/ODBC drivers, which are optimized for performance and tailored to specific data sources. Sync offers pre-built connectors for over 250 data sources that include most major CRMs (like Salesforce and HubSpot), ERPs (like NetSuite and SAP), and custom APIs, as well as supporting a wide range of destinations, from traditional databases like SQL Server, Oracle, and PostgreSQL, to modern cloud platforms like Snowflake, Databricks, or Microsoft One Lake.
Deployment
When it comes to deployment options, Snowflake Openflow is currently only available in an AWS BYOC deployment model. Other deployment options are not publicly released, but it is anticipated that other options, such as Azure BYOC and Snowflake-hosted deployments, will be available in the near future.
CData Sync offers broad deployment flexibility, whether on-premises, BYOC (AWS and Azure), cloud-hosted, or in a hybrid environment. This flexibility enables users to align their deployment with their current data ecosystem, enhancing their existing workflows and investments without requiring a complete replacement.
Connector ecosystems and development extensibility
With Snowflake Openflow still being in early public preview, it currently supports a limited number of connectors (about 20 documented options), with more expected to be released in the future. These connectors are versioned Apache NiFi flow definitions, built using open-source and proprietary NiFi components. Core capabilities like change data capture (CDC) are supported for select database connectors such as Snowflake, SQL Server, MySQL, and PostgreSQL.
CData Sync offers over 250 production-ready connectors that are built on the mature and extensible CData Driver framework. This connector library provides high-performance access to a wide range of sources, including cloud-based CRMs, legacy on-premises databases, custom APIs, and even flat files like Excel or CSV. Because each connector is fully supported and source-specific, teams can onboard new data sources quickly and reliably without the need for writing custom code or navigating open-source dependencies.
CData Sync also offers additional extensibility by supporting Reverse ETL out of the box to a variety of operational systems, such as Salesforce, HubSpot, or Dynamics 365. This helps teams close the loop on their data pipelines, allowing them to push enriched data from Snowflake and other databases back to those operational systems to keep frontline teams equipped with the insights they need to perform efficiently.
Cost models and pricing transparency
Snowflake Openflow
Openflow uses a credit-based pricing model that is based on data volume and the number of virtual CPU (vCPU) cores allocated for processing. Because Openflow is currently only available as an AWS BYOC deployment, customers also incur additional infrastructure costs for deployment through their cloud provider.
CData Sync
CData Sync offers connection-based pricing, where the cost is determined by the number of connections used in the Sync instance, no matter the data volume moved. This model differs from usage-based ETL tools and provides predictable, scalable costs even as data consumption grows.
Ideal use cases: When to choose each
Snowflake Openflow
For organizations that are deeply integrated with the Snowflake ecosystem, Snowflake Openflow could be a natural fit. It enables Snowflake to be an all-in-one solution to stream structured and unstructured data into Snowflake. The platform provides native integration with Snowflake's Cortex AI tools, and because it is built on an open-source foundation, users can extend its capabilities in the future by adding custom connectors and logic, allowing them to tailor the deployment to their specific needs as their data pipelines scale. Openflow makes the most sense when your data ingestion, processing, and analytics are all Snowflake-native.
CData Sync
CData Sync is best suited for organizations that are seeking broad platform compatibility, cost predictability, and deployment flexibility. With its extensive connector library and hybrid environment support, Sync enables seamless data movement from any source to any destination and avoids single vendor lock-in. It's ideal for augmenting and enhancing existing workflows and investments, without the need to replace or adjust any current infrastructure.
Expand your Snowflake connectivity with CData
Evaluate your integration priorities—whether AI-powered analytics in Snowflake or hybrid enterprise data movement. Explore CData Sync to see how it delivers flexible, predictable integration across any architecture:
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