Fuel Your AI With Datavolo and Apache NiFi
Datavolo (powered by Apache NiFi) is built to rapidly accelerate the creation, management, and observability of multimodal data pipelines to AI Systems. Fundamentally data is created in different places than it is consumed and Datavolo fills that gap. Over 300 connectors and processors are provided out of the box with limitless expansion capabilities with processors written natively in Python or Java. Don’t let data engineering be a bottleneck to harnessing the power of Generative AI!
Build Data Pipelines in Minutes (or seconds!), Not Days
Datavolo allows users to rapidly build data pipelines either with a no-code visual user interface or even with natural human language (as in this demo). See why the largest, most complex, and most secure data pipelines in the world are built on NiFi…… in minutes.
Agility to Quickly Adapt to Rapidly Evolving AI Tech Ecosystem
Datavolo allows you to build your data pipelines once and easily iterate and adapt to the changing AI ecosystems. Want to try out a new LLM or AI System without impacting your current pipelines? No problem. Want to iterate on chunking or parsing strategies and tools? No problem. Want to experiment with best of breed vector databases? Datavolo has that covered too.
Datavolo is the ONLY data pipeline solution for ALL multimodal data
Modern Data Pipeline vendors are built primarily on an ELT architecture heavily oriented around high volumes of low complexity, row oriented data. Due to this limitation, companies are forced to write their own custom coded data pipelines to handle multimodal data and the processing necessary for consumption of this data. Datavolo is powered by Apache NiFi which was built at the NSA specifically to handle large, complex, multimodal data and is suited to handle any data you have. This gives Datavolo the proper architecture and power to handle the data types of today (and tomorrow).
Easily Implement Today’s Advanced RAG Patterns
Datavolo is built to handle data pipelines for not only all modalities of data but all implementation patterns of AI Systems. Today those are commonly various types of Naive or Advanced RAG patterns, agentic architectures, or full chains of integrated AI systems. As AI Systems evolve, Datavolo provides the flexibility to deliver the data where it needs to go and in whatever format it needs to get there.
Observability, Security, and Governance at its Core — Out of the Box
Datavolo provides enterprise grade protections and observability with every flow. Lineage is a given. You can trust that your data is secure and untampered with and your AI systems can cite back to the origins of their responses. End hallucinations by providing the full context to AI Systems you can trust.
Choosing Datavolo was an easy choice as working with their team and technology was able to 10x the speed by which we deliver new features to our customers. We work with highly regulated customers, as does Datavolo, and that expertise is invaluable.
How does Datavolo differentiate from Open Source Apache NiFi?
Datavolo is focused on many enhancements to solve for the unique challenges of Generative AI data pipelines but generally are making major improvements to the usability and value of NiFi for enterprises. One such feature we have already released publicly is a GenAI based Flow Generator that allows you to write in your native speaking language and have that natural language translated to a NiFi flow as output. Since the founding team is the core engineering team of Apache NiFi, Datavolo is uptaking releases immediately as released in the community. This means we are based on Apache NiFi 2.0 which has major enhancements such as the ability to natively create processors in Python in addition to Java. We also are seeing strong interest in adoption in NiFi 2.0’s Open Telemetry processing capabilities. Finally, Datavolo provides a secure, containerized version of Apache NiFi that will be able to be deployed in SaaS or Bring Your Own Cloud form factors (including Private Cloud Kubernetes environments).
How does Datavolo differentiate from Apache Airflow?
How does Datavolo differentiate from Apache Kafka?
Apache Kafka is a distributed streaming platform capable of handling very high throughput, reliability, and scalability. However, Kafka does not have the ability to handle very large objects which severely limits its capability to process streams of multimodal data which, by its nature, is very large and complex. Datavolo is powered by Apache NiFi was built ground up to handle all types of multimodal data.