Druid community meetup (feat. Kafka & Memgraph)

Join us for an in-person meetup happening in London after Kafka Summit! Learn about building apps with Druid + Kafka, how to deploy a real-time analytics platform in 20 minutes or less, and graph-based stream processing with Kafka. Please register to secure your spot!

AGENDA:
6–6:30pm: Pizza, adult beverages & networking
6:30–7:10pm: Analytics for Lazy People
7:10–7:40pm: Upstream Processing with Apache Kafka for Immediate Intelligence with Apache Druid
7:40–8:30pm: Graph-based Stream Processing with Kafka

Talk #1: Analytics for Lazy People

Talk abstract: Deploying an analytics platform that enables interactive conversations with combined real-time and historical data sounds hard to do. But it really isn’t. Join Darin Briskman from Imply to learn how you can set up and deploy a real-time analytics platform in 20 minutes or less. Hard work may be good, but smart work is better!

Speaker bio:
Darin Briskman is Director of Technology at Imply, where he helps developers create modern data applications. He began his career at NASA in the 1980s (ask him about rockets!), and has been working with large and interesting data sets ever since. Most recently, he's had various technical and leadership roles at Couchbase, Amazon Web Services, and Snowflake. When he's not writing code, Darin likes to juggle, blow glass (usually not while juggling), and working to help children on the autism spectrum learn to use their special abilities to work better with the neuronormative.

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Talk #2: Upstream Processing with Apache Kafka for Immediate Intelligence with Apache Druid

Talk abstract: Applications built with Apache Druid databases are revolutionary: a real-time event hub and processor such as Apache Kafka is an essential component that keeps the user up-to-date and the statistics meaningful. Peter Marshall (Director, Developer Relations at Imply) talks about the importance of fast upstream processing and delivery to modern “immediate intelligence” applications, drilling into some examples of work done upstream of Apache Druid.

Speaker bio:
Peter Marshall is an award-winning speaker who leads community developer advocacy at Imply, a company founded by the original developers of Apache Druid. He has 20 years architecture experience in CRM, EDRM, ERP, EIP, Digital Services, Security, BI, Analytics, and MDM. He is TOGAF certified and has a BA (hons) degree in Theology and Computer Studies from the University of Birmingham in the United Kingdom.

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Talk #3: Graph-based Stream Processing with Kafka

Talk abstract: Graph analytics have found their way into every major industry, from marketing and financial services to transportation. Fraud detection, recommendation engines, and process optimization are some of the use cases where real-time decisions are mission-critical, and the underlying domain can be easily modeled as a graph.

By ingesting data with Apache Kafka and applying graph-based stream processing in real-time, you can perform near-instantaneous graph analytics on vast amounts of data. When it comes to complex networks, it’s often necessary to perform graph algorithms such as calculating the PageRank, identifying communities, traversing relationships, etc. Memgraph is an open-source streaming platform that can be used to analyze graph-based data models and accelerate application development.

Graph analytics can provide insights into complex networks that would otherwise require resource-intensive computations. When connecting a Kafka data stream to Memgraph, you only need to create a transformation module that will map incoming messages to the property graph model. This data can then be traversed and analyzed using the Cypher query language without having to implement custom algorithms or relying on development-heavy solutions. MAGE (Memgraph Advanced Graph Extensions) is a graph library that works well with Kafka-powered systems and contains graph algorithms meant for analyzing streaming data. Besides stream processing, you can also utilize standard graph algorithms from the MAGE library to explore the stored data.

Speaker bio:
Ivan Despot is a Developer Relations Engineer at Memgraph. His passion for mathematics and graph theory inspired him to become part of the Memgraph team and start contributing to the field of graph analytics. Besides graph-based technologies, he is also interested in streaming platforms, stream processing and event-driven development.

Speaker bio:
Katarina Šupe is a Developer Relations Engineer at Memgraph. Her journey there started with a summer internship, and her mathematics and computer science background was a perfect match to work in Memgraph. She enjoys contributing to different areas and exploring new real-time data visualization technologies. She sees the graph world as a future of data analytics due to the variety of algorithms used for stream processing.