49:00
Gimel: PayPal’s Analytics Data Platform
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.
37:28
Introducing FlureeDB, The World's First ACID-Compliant Blockchain Database
Brian Platz introduces FlureeDB, a graph-style database for building blockchain applications.
30:17
Delivering the Power of Data Using Spring Cloud Data Flow and DataStax Enterprise Cassandra NoSQL Database
Gilbert Lau and Wayne Lund talk about using SCDF on PCF for microservice scaling and pipelining data into Cassandra.
34:32
Beyond Rapid Development: Continuous Operations and Telemetry / Monitoring with MongoDB on PCF
Jason Mimick demos using PCF to deploy geo distributed, horizontally scalable MongoDB Enterprise deployments through a self service model.
45:57
Taming Distributed Stateful Pets with Kubernetes
Matthew Bates,James Munnelly explain how to use StatefulSet and dynamic volume provisioning to manage the lifecycle of distributed and secure Cassandra clusters with the open source project Navigator.
28:36
Reactive Data Access with Spring Data
Christoph Strobl and Mark Paluch discuss non-blocking data access using Spring Data for NoSQl data stores and Project Reactor.
01:00:01
Handling Billions of Edges in a Graph Database
Michael Hackstein discusses graph databases, the current scalability problems and their solutions.
39:35
Do We Need Another Key-Value Store?
Hendrik Muhs introduces Keyvi, a key-value store based on 'finite state', describing the concepts, explaining what makes it different and where it is useful.
01:09:27
Applied Distributed Research in Apache Cassandra
Jonathan Ellis explains the challenges and successes Cassandra has had in creating transactions, materialized views, and a strongly consistent cluster membership within this peer-to-peer paradigm.
47:56
In-Memory Caching: Curb Tail Latency with Pelikan
Yao Yue introduces Pelikan - a framework to implement distributed caches such as Memcached and Redis. She discusses the system aspects that are important to the performance of such services.
49:40
Causal Consistency for Large Neo4j Clusters
Jim Webber explores the new Causal clustering architecture for Neo4j, how it allows users to read writes straightforwardly, explaining why this is difficult to achieve in distributed systems.
47:03
Real-Time Recommendations Using Spark Streaming
Elliot Chow discusses the data pipeline that they built with Kafka, Spark Streaming, and Cassandra to process Netflix user activities in real time for the Trending Now row.
CONTENT IN THIS BOX PROVIDED BY OUR SPONSOR
FEATURED CONTENT:
The Architecture of a Real-Time Operational DBMS
Years ago, Aerospike’s engineering team set out to build a distributed database system that handles real-time workloads smoothly and provides a high level of fault tolerance. Learn how they built a high-performance, distributed database to handle the needs of today’s interactive online services.
A NoSQL Database Architecture for Real-Time Applications
Learn about a new kind of NoSQL database architecture that’s simple, cost-effective and that delivers speed at scale for real-time applications. This new architecture delivers predictable performance while using up to ten times fewer servers than most other databases.
When, Where & Why to Use NoSQL?
Download this white paper and learn the biggest challenges of managing big data, database requirements for dealing with big data, and how NoSQL databases address these challenges.
Maximizing the Value of Your Operational Data
This paper introduces key technologies that Aerospike clients are using to modernize their data management infrastructures, process large volumes of operational data in real time, and realize rapid read/write speeds without extensive tuning or a separate data cache.
Follow Aerospike on:
