This Week in Neo4j: Batch vs. Stream, UX Survey, Kafka Example, Jupyter/Docker for Data Science, Deep Learning

Neo4j is continually improving its user experience, and users are encouraged to provide feedback. The company has shared various resources, including a blog post on setting up a Docker environment for Neo4j with Jupyter Lab, an example of moving data from Kafka to Neo4j, and a presentation on Lightning Fast Zero to Production with Spring, Neo4j, and jHipster. A featured community member, Camilla Dal Rio, will be presenting at NODES 2021 on using machine learning and MLOps with graph databases. The company is also seeking user input to improve its UX for developers and data scientists, offering compensation for participants. Additionally, users can watch a recording of the NODES 2020 presentation on Lightning Fast Zero to Production with Spring, Neo4j, and jHipster.

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