Name: Apache Ignite in the Big Data Ecosystem
Start: 2018-10-24T18:00:00-04:00
End: 2018-10-24T20:00:00-04:00
Location: WeWork 575 Fifth

Target Audience: Intermediate

Agenda:

6:00 PM - 6:30 PM: Food, drinks, mingling

6:15 PM - 6:30 PM: Artem Ervits Announcements, call for presenters, future events

6:30 PM - 7:15 PM: Gabriel Jimenez - Introducing Big-SQL: Apache Ignite + Apache Phoenix on Spring Boot

Apache Phoenix combines standard SQL and JDBC APIs with the scalability of HBase’s NoSQL data store to provide the best of both worlds. Thinking along the same vein, We looked to combine Apache Phoenix with Apache Ignite as a way to offer in-memory performance
with large volumes of data including support for 3D-XPoint memory. Ignite exposes database caching functionalities as a key-value in-memory data grid that plugs itself seamlessly into a distributed system configuration with the added support of distributed
UDF's on SQL. All in all, both projects packaged together neatly in a Spring Boot application make for a high performance, scalable storage solution for users without straying from the comfort of SQL. Spring Boot enables an elegant and standards compliant usage pattern for Security, Caching, Metrics, Session management and many more necessary features. In this talk we will divulge the internal workings of the project, discuss benchmarks and showcase a few live demos.

7:15 PM - 8:00 PM: Akmal Chaudhri - Best practices for stream ingestion, processing and analytics using in-memory computing.

This talk would feature Apache Ignite, an open source memory-centric distributed database, caching, and processing platform used for transactional, analytical and streaming workloads -- delivering in-memory speeds at petabyte scale. https://ignite.apache.org. In this talk, Akmal Chaudhri will share the best practices used for real-time stream ingestion, processing and analytics using Apache Ignite, Apache Kafka, Apache Spark and other technologies. Akmal, will explain how to: * Optimize stream ingestion from Kafka and other popular messaging and streaming technologies * Architect pre-processing and analytics for performance and scalability * Implement and tune Apache Ignite and Spark together * Design to ensure performance for real-time reports By the end of Akmal's talk, you’ll understand best practices for stream ingestion, processing and analytics using in-memory computing.

Wrap Up Q&A

Note:

The building entrance is on 47th between 5th and Madison
Everyone must check-in with building’s security in the Lobby before being directed to the 14th floor (main community floor).

Bio:

Gabriel Jimenez, an infrastructure developer at Bloomberg. Working mainly in the realm of distributed systems and addressing ETL challenges. This involves working closely with technologies such as Apache HBase, Apache Phoenix, Apache Ignite, and the Spring
ecosystem.

Akmal Chaudhri is GridGain’s technology evangelist. His role is to help build the global Apache Ignitecommunity and raise awareness through presentations and technical writing. Akmal has over 25 years experience in IT and has previously held roles as a developer, consultant, product strategist and technical trainer. He has worked for several blue-chip companies such as Reuters and IBM, and also the Big Data startups Hortonworks (Hadoop) and DataStax (Cassandra NoSQL Database).

Artem Ervits

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