Dear Big Data Beers Community,
we are excited to announce the next meeting. This time we have a wonderful location provided by Amazon Berlin (thanks!).
Furthermore we have two interesting and distinct hot databases to be presented.
BigchainDB and CortexDB.
Happy to welcome you all!
Title: Blockchains in a Big Data World
Speaker Trent McConaghy
Abstract: “Big data” distributed databases emerged as new storage paradigm, and quickly rose to prominence. Now we have “blockchain” storage, with promising applications. Yet blockchains have been strangely separate from the Big Data database world. What if they weren’t? What if there was a way to reconcile blockchains with Big Data? This talk describes how, using the example of BigchainDB. BigchainDB starts with a “big data” distributed database and adds blockchain characteristics of decentralized control, greater tamper-resistance, and the ability to issue & transfer assets.
Bio: Trent McConaghy is co-inventor of the BigchainDB blockchain database. Previously, he co-founded Solido Design Automation, which uses big data & large-scale machine learning to help drive Moore’s Law. Trent has written two critically-acclaimed books on machine learning and circuits, in addition to 50 papers+patents. He has given keynotes & invited talks at MIT, Columbia, Berkeley, JPL, Nvidia, and more.
“CortexDB – a NoSQL Database inspired by human brain research”
Speaker: Jan Buss, Michael Backhaus
The CortexDB world’s only database provides automatic transformation of imported raw data in the highest (6th) Normal Form.
This results in a number of significant advantages (e.g. Semantic Network) for the development of analytical applications in Big Data environments. Jan Buss (ceo) and Michael Backhaus (core developer) will show, based on live demos, how the digital trends and challenges to the current software development can be solved with Cortex. We are looking forward to a lively discussion.
CortexDB Technology Features:
• CortexNF6: Automatic transformation of the raw data in the highest (6) Normal Form (Entity Relationship Model) / Extremely fast context queries on a “low footprint” on top Big Data
• Schema-less multi-model NoSQL technology (Key value; Document store; Graph DB; Multi value DB; Column DB)
• temporal database technology (bi-temporal) with transaction date and validity period of data (Bitemporal Data)