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49:00
AI, ML & Data Engineering Follow 816 Followers

Gimel: PayPal’s Analytics Data Platform

Posted by Deepak Chandramouli  on  Jun 13, 2018 Posted by Deepak Chandramouli Follow 0 Followers  on  Jun 13, 2018

Deepak Chandramouli introduces and demos Gimel, a unified analytics data platform which provides access to any storage through a single unified data API and SQL.

28:36
Java Follow 894 Followers

Reactive Data Access with Spring Data

Posted by Christoph Strobl  on  Mar 10, 2018 Posted by Christoph Strobl Follow 0 Followers , Mark Paluch Follow 0 Followers  on  Mar 10, 2018

Christoph Strobl and Mark Paluch discuss non-blocking data access using Spring Data for NoSQl data stores and Project Reactor.

54:36
AI, ML & Data Engineering Follow 816 Followers

ScyllaDB: Achieving No-Compromise Performance

Posted by Avi Kivity  on  Mar 07, 2017 1 Posted by Avi Kivity Follow 0 Followers  on  Mar 07, 2017 1

Avi Kivity discusses ScyllaDB, the many necessary design decisions, from the programming language and programming model through low-level details and up to the advanced cache design, and more.

01:06:28
AI, ML & Data Engineering Follow 816 Followers

But I Need a Database that _Scales_

Posted by Aaron Spiegel  on  Dec 11, 2016 2 Posted by Aaron Spiegel Follow 0 Followers  on  Dec 11, 2016 2

Aaron Spiegel reviews common scaling techniques for both relational and NoSQL databases, discussing trade-offs of these techniques and their effect on query flexibility, transactions and consistency.

50:44
AI, ML & Data Engineering Follow 816 Followers

Ingest & Stream Processing - What Will You Choose?

Posted by Pat Patterson  on  Aug 14, 2016 1 Posted by Pat Patterson Follow 0 Followers , Ted Malaska Follow 0 Followers  on  Aug 14, 2016 1

Pat Patterson and Ted Malaska talk about current and emerging data processing technologies, and the various ways of achieving "at least once" and "exactly once" timely data processing.

50:32
AI, ML & Data Engineering Follow 816 Followers

GoshawkDB: Making Time with Vector Clocks

Posted by Matthew Sackman  on  May 29, 2016 Posted by Matthew Sackman Follow 0 Followers  on  May 29, 2016

Matthew Sackman discusses dependencies between transactions, how to capture these with Vector Clocks, how to treat Vector Clocks as a CRDT, and how GoshawkDB uses them for a distributed data store.

01:26:11
Java Follow 894 Followers

Working with Databases & Groovy

Posted by Paul King  on  Jan 22, 2016 Posted by Paul King Follow 0 Followers  on  Jan 22, 2016

Paul King reviews the features in Groovy which make it easy to work with databases - Groovy SQL, datasets -, and working with NoSQL databases such as MongoDB and Neo4J.

24:57
NoSQL Follow 86 Followers

Modeling Complex Game Economy with Neo4j

Posted by Yan Cui  on  Oct 13, 2015 Posted by Yan Cui Follow 0 Followers  on  Oct 13, 2015

Yan Cui shares lessons learned using Neo4j to model the in-game economy of the "Here Be Monsters" game and automate the balancing process.

44:53
Big Data Follow 120 Followers

Ground-up Introduction to In-memory Data

Posted by Viktor Gamov  on  Oct 10, 2015 Posted by Viktor Gamov Follow 0 Followers  on  Oct 10, 2015

Viktor Gamov covers In-Memory technology, distributed data topologies, making in-memory reliable, scalable and durable, when to use NoSQL, and techniques for Big In-Memory Data.

53:05
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LDAP at Lightning Speed

Posted by Howard Chu  on  Jul 05, 2015 Posted by Howard Chu Follow 0 Followers  on  Jul 05, 2015

Howard Chu covers highlights of the LMDB design and discusses some of the internal improvements in slapd due to LMDB, as well as the impact of LMDB on other projects.

49:04
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Beating the Traffic Jam Using Embedded Devices, OPC-UA, Akka and NoSQL

Posted by Kristoffer Dyrkorn  on  May 10, 2015 Posted by Kristoffer Dyrkorn Follow 0 Followers  on  May 10, 2015

Kristoffer Dyrkorn presents the experiences gained by the Norwegian Public Roads Administration in building a new infrastructure for road traffic measurements.

57:10
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Customer Insight, from Data to Information

Posted by Thore Thomassen  on  Mar 27, 2015 Posted by Thore Thomassen Follow 0 Followers  on  Mar 27, 2015

Thore Thomassen shares from experience how to combine structured data in a DWH with unstructured data in NoSQL, and using parallel data warehouse appliances to boost the analytical capabilities.

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