Technical Presentations About GridGain and Apache Ignite

The technical presentations below will help you understand, configure, and deploy the GridGain® and Apache® Ignite in-memory computing solutions. The presentations cover topics including in-memory computing, in-memory databases, stream processing, data lake acceleration, machine learning, deep learning, and how to apply these technologies and others to power your organizations’ digital transformation. These technical presentations have been developed and presented by GridGain in-memory computing experts.


During this 1-hour webinar, we explain and demonstrate how to build a fast data solution that can receive endless IoT-generated streams and process them in real-time using Apache Ignite's distributed in-memory computing platform. In particular, you will learn the following:
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During this webinar, we will discuss the use of in-memory computing to support the following:
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This webinar discusses how in-memory computing using Apache® Ignite™ can overcome the performance limitations common to microservices architectures built using traditional database architectures. 
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During this webinar, we will discuss opportunities to modernize payments infrastructures using in-memory computing to bring about reliable, scalable, high-performing and secure payment solutions.  Topics include:
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Learn how the world’s largest financial institutions use the power of in-memory computing for:
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Validating financial transactions is necessary to satisfy demanding regulatory and client protection requirements. It requires monitoring, collecting and analyzing real-time data from multiple, disparate sources.
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Topics covered during this webinar will include: How GridGain and Apache Ignite can integrate with your most critical .NET apps to achieve incredible speed and scale How to interoperate between Java and .NET Sample use cases and code examples How to get started and keys to successful deployment
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This webinar will show you how: To incorporate GridGain and Apache Ignite into your data warehouse architecture To bring extreme scale and speed to your Hadoop, Spark or RDBMS GridGain is used by clients to meet current and future data performance needs
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Eric Karpman, a 30-year veteran of the financial services industry, shares how some of the world’s largest financial institutions use in-memory computing to address the challenges of high frequency trading. You will learn how to leverage in-memory computing to solve high frequency trading challenges and how GridGain and Apache® Ignite™ can address your specific needs…
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This webinar will explain in detail how IgniteRDD — an implementation of native Spark RDD and DataFrame APIs — shares RDD state across Spark jobs, applications and workers. We demonstrate how IgniteRDD, with its advanced in-memory indexing capabilities, allows execution of SQL queries much faster than native Spark RDDs or Data Frames.
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In this one-hour webinar you will learn how GridGain can turbocharge your Cassandra cluster without sacrificing availability guarantees. You will hear: An overview of the GridGain architecture How to deploy GridGain in minutes on top of Cassandra How companies use this powerful combination to handle extreme OLTP workloads
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This webinar covers: In-Memory Options for products such as Oracle Database 12c and Microsoft SQL Server In-Memory Databases such as VoltDB, MemSQL, and SAP HANA In-Memory Data Grids such as Hazelcast, Oracle Coherence, and GigaSpaces In-Memory Computing Platforms and Fabrics such as GridGain
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