The first step in building highly effective NiFi dataflows: learn about the  QueryRecord Processor. #nifi #dataflow #apachenifi #dataengineering link.medium.com/R5FSM4kdwvb

Fun with Apache NiFi: Using UpdateDatabaseRecord for Schema Migration and Database Replication funnifi.blogspot.com/2022/12/using-…

The next post in the "Building an Effective NiFi Flow" series is up This time it will focus on PartitionRecord and the power and easy of use that it brings #nifi #apachenifi #dataflow #dataengineering #partitionrecord link.medium.com/DZBb240HHvb

Apache NiFi is the perfect tool for AI/ML product managers looking to manage and automate data flows in real time! It cuts down the pipeline build time for AI products!

Why You Should Learn Apache NiFi 🚀 Hey, you gotta check out Apache NiFi - an open-source data integration tool that makes it easy to automate data flow between different systems! This is a must-have tool for all data engineers and scientists working with data. 💻💡

NiFi's ReplaceText processor can be a powerhouse for data transformation Learn some tips & tricks for using effectively and efficiently in my latest blog post: medium.com/@nifi.notes/bu…

Apache NiFi 1.21.0 released! Mostly focused on stability, security and preparing for the NiFi 2.0 line including more than 120 resolved JIRAs. Download nifi.apache.org/download.html

A Python API is coming to NiFi! Want a sneak peek? I put together a video that demos how it will work, and how to build a Processor in Python. Oh, and I provide a build that you can use to try it out today! youtu.be/9Oi_6nFmbPg #python #nifi #dataflow #dataengineering

Modernizing Streaming Encryption with age in Apache NiFi exceptionfactory.com/posts/2023/12/…

New year, new website design! Thanks to a collaborative effort from several designers and developers, the Apache NiFi project website has a new look, with more prominent links to downloads, documentation, and source code! nifi.apache.org

A fitting new look for the NiFi website as the NiFi 2.0 M1 release gains traction. The new python integration and alignment to Generative AI use cases is huge for our community!

At the enterprise level today every company is a data company and the only constant is change itself.  Generative AI is our latest compelling reminder. NiFi was built for this very opportunity. datavolo.io/2024/01/why-ge…

The response from long time Apache NiFi users already as well as new ones tells us we are on the right track Datavolo to help a lot of organizations get their unstructured data to and through these powerful LLMs as well as help orchestrate other aspects of Gen AI data patterns

Ever dreamed of building data pipelines by just describing the flow? Well, now you can! 🤯 Datavolo's new Generative AI features allow you to describe a dataflow and we'll will build it for you! Check it out: youtu.be/3oRnUdE7x7w

This is the future of data pipelines. Auto generate NiFi flows from natural language youtube.com/watch?v=3oRnUd… #ApacheNiFi #dataflows #data

NiFi-LangChain, designed for constructing Large Language Model (LLM) pipelines within Apache NiFi using the composable LangChain Expression Language (LCEL), is now available on GitHub: github.com/lifan0127/nifi…

Gone are the days of simply managing data—AI has ushered in the era of intelligently leveraging data. We're thrilled to support Joe Witt & Luke Roquet as they embark on the next phase of the Datavolo journey. By quentinclark & Max Rimpel ↓ generalcatalyst.com/perspectives/o…

We're pleased to announce our joint investment in Datavolo along with General Catalyst and others to help revolutionize data pipelines with #AI. Read more at SiliconANGLE: spr.ly/6011Z0nv3

I'm excited to welcome Joe Witt, Luke Roquet and the whole team at Datavolo to the GC family! 🙌 We're thrilled to partner on this journey with you 😊 Read more about what got us excited below 👇 lnkd.in/g3yfV4HY cc: General Catalyst , quentinclark

An expensive Kafka cluster sells for $1M. Cheap Kafka sells for … $220M The story of how Confluent acquired WarpStream after just 13 months of operations 👇