Peter Vescuso, CMO, VoltDB and Mike Gualtieri Principal Analyst, Forrester Research talk about the latest on the streaming analytics market, in-memory database technology, and the emergence of ‘translytics’. Also hear how the latest release of VoltDB, the in-memory operational database, simplifies the distributed system complexity of building high-speed data pipelines with rapid ingestion of data, real-time analytics, Apache Kafka support, and Elasticsearch support.
Real-time analytics on streaming data is a strategic activity. Enterprises that can tap streaming data to uncover insights and take action faster than their competition gain business advantage. Join John Hugg, Founding Engineer, VoltDB and Pethuru Raj Chelliah and Skylab Vanga, Infrastructure Architect and Specialists, IBM SoftLayer to learn how VoltDB enables high performance and real-time big data analytics in the IBM SoftLayer cloud.
The data you need to manage isn’t getting smaller, or slower. It’s a snowball, compounding in both speed and volume. If you’re building applications on fast, streaming data, you need to analyze it, gain insight and take action on it now, not at the end of a batch job. Listen to Peter Vescuso discuss the lessons learned from an actual real fast data use case.
Streaming data can translate into big revenue if your enterprise is designed to handle it correctly. Listen as Peter Vescuso, VoltDB CMO and Anders Ekman, President, DataMentors discuss how to enhance big data with real-time behavioral data, and implementing a Data-as-a-Service solution to help clients access real-time data for immediate, actionable insight. They will also discuss a use case highlighting how integrating real-time behavioral data into proactive marketing campaigns can transform the marketplace.
A software stack is emerging for streaming data applications that process high velocity flows of data in motion, or “fast data.” Similar to the LAMP stack for web servers, the Fast Data Stack describes what’s needed to meet the requirements for fast data applications: to grab real-time data and output recommendations, decisions and analyses in milliseconds. Listen as Ryan Betts describes the architecture of the Fast Data Stack which include ingestion, real-time analytics and decisions, and data export. He’ll explain how new applications can benefit from this architecture when processing real-time data, and providing decisions and analyses in milliseconds.
In this webcast, CMO Peter Vescuso and Dr. Michael Stonebraker discuss the new corporate data architecture and the necessary technology components for facing this data management challenge. Listen as they discuss the “one-size-never-fits-all” perspective for developing the ideal architecture for managing, and maximizing the value of fast, big data in your organization.
Writing applications on top of streaming data requires both scalable high throughput event processing, as well as efficient large volume storage. At scale, this requires combining best-in-class tools to create a complete solution. Real-time applications and the increasingly fast data streams created by personalized devices, IoT, and M2M, exceed the processing and storage capacity of legacy databases.
In this webinar, VoltDB Software Engineer, John Hugg discuss how to ingest large volumes of fast-moving, streaming data, and how to interact and process the data stream to support analytics and decision-making. You will also learn about creating new applications that support fast, reliable handling of messages all with a scale-out architecture and without sacrificing data guarantees.
Big Data is transforming the way enterprises interact with information, but that’s only half the story. The real innovations are happening at the intersection of Fast Data and Big Data. Why? Because data is fast before it’s big. Fast Data is generated by the explosion of data created by mobile devices, sensor networks, social media and connected devices – the Internet of Things (IoT).
In this webinar Rusty Ross, Solutions Architect, Full 360, Inc. and Peter Vescuso, CMO, VoltDB present a case study of the fast data infrastructure developed for one of the largest and most successful loyalty programs in the world. Using Docker, the solution leverages AWS Elastic Load Balancing to automatically distribute incoming application needs without manual intervention. The result was an integrated, highly scalable 10 million-person loyalty program that can turn data into deployed services quickly and easily; enabling them to respond rapidly to changing needs and insights.