We’re excited to announce Snowflake’s intent to acquire Datavolo, an open and extensible data integration and orchestration platform built by the co-creators of Apache NiFi. This acquisition marks a significant step in expanding Snowflake’s capabilities for data engineers, focusing on data integration in the bronze layer. With this acquisition1, Snowflake will further accelerate solutions for customers’ multimodal data integration needs for AI, analytics and apps. Regardless of the source system, data type, velocity or volume, we aim to provide an open and highly extensible managed-platform experience that enables seamless bi-directional data integration with Snowflake, other popular data lakes or cloud storages with a radically simple and extraordinary price/performance profile. Developers can say goodbye to fragmented data pipeline experiences tied to specific sources and destinations — Snowflake, powered by Datavolo, will ensure unified and streamlined data connectivity for all their data integration needs.
1. Unstructured data and streaming made simple
Datavolo specializes in multimodal data integrations at high velocity. This acquisition will help your data engineering teams easily and securely process unstructured multimodal data and streaming workloads in Snowflake. With Datavolo’s managed offering, your data science teams can build pipelines that handle complex unstructured data — documents, logs, multimedia files for AI solutions. Datavolo also inspects document metadata so that when authorization changes occur on the files in the source location, access controls can be enforced at the AI app layer, providing end-to-end secure RAG applications. Datavolo’s streaming data connectivity with Kafka, Kinesis, Flink, etc., will further unlock real-time AI driven insights.
2. Hybrid deployment with BYOC for complete control
With Datavolo, Snowflake will offer a hybrid deployment model, allowing data engineers to choose where to run their data integration stack. You can run the platform entirely within Snowflake’s VPC for a streamlined experience or operate within your own VPC for complete control via the BYOC (Bring Your Own Cloud) model. This flexibility will allow organizations to manage data on their terms, ensuring that data integration and transformation happen securely and efficiently, whether in Snowflake’s VPC environment or in their own VPC.
Whether you choose Snowflake’s VPC or BYOC, Snowflake will continue to offer a seamless authoring, observability and execution experience, along with Snowflake’s simplicity, security and governance.
3. Extensible by design
Datavolo’s extensible processor framework allows data engineers to tailor workflows to meet specific business needs. In addition to first-party integrations for leading SaaS apps, OLTP and vector databases, streaming platforms, CMS and logs sources, developers and Snowflake partners can build custom ingestions from any source they choose — all directly within the platform. Snowflake will offer this extensible platform to power the experiences of your highly customized data pipeline needs.
4. Open at the core and enterprise ready
Datavolo’s foundation in Apache NiFi aligns with Snowflake’s commitment to open standards and interoperability, and our investments in Apache Iceberg, Apache Polaris (incubating) and Arctic. We’re building a data engineering ecosystem that empowers engineers to connect, customize and control their data using open source frameworks and tools they already love. By bringing the Datavolo team and the creators of Apache NiFi to Snowflake, we’re expanding our open source capabilities to provide a data integration experience that connects any source to any sink. Once fully integrated, this managed service will offer Snowflake’s out-of-the-box security, governance, observability and maintainability solutions to make this platform a trusted choice for all developers.
With Datavolo, Snowflake will deliver a fully managed, extensible and open data engineering platform that offers end-to-end support for every data, workload and deployment model. We’re excited to bring these powerful capabilities to our data engineering community in the coming months, and we can’t wait to see what you build on this powerful platform.
1 Closing of the acquisition is subject to customary closing conditions.
