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.
In-memory database technology enables a new wave of fast data use cases that are extremely challenging and in some cases not possible with older technologies. In this webinar, Noel Yuhanna, Principal Analyst of Forrester Research, and VoltDB CMO, Peter Vescuso will discuss the latest market and data access technology trends, the new use cases these trends enable, and the implications for business and IT leaders.
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 Ryan Betts, CTO at VoltDB, will explain why streaming aggregation is a key to streaming analytics. He will also address how SQL can be used in combination with streaming aggregation, and the benefits of up-to-date analytics for per-event transactions and insights.
Dr. Michael Stonebraker will share his "one-size-doesn’t-fit-all" perspective when it comes to picking the right tool for the job. He will explain the fast data stack, why traditional RDBMS’s fall short and how a modern in-memory SQL, ACID compliant, database with a scale-out architecture is the right choice for enabling fast data applications. Then John Hugg provides the “proof in the pudding” with a step-by-step review of his Unique Devices application, which performs real-time analytics on fast moving data. It's a representative implementation of the speed layer in the Lambda Architecture with the logic captured in just 30 lines of code.
Presented by Prateek Kapadia, CTO, Flytxt and Ryan Betts, CTO, VoltDB.
Prateek and Ryan will highlight the technology stack for Fast + Big data and iterative analytics using Hadoop and VoltDB.
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.
VoltDB CTO, Ryan Betts and Flytxt CTO, Prateek Kapadia discuss how the modern telecommunications data center environment must cater to billions of high frequency events daily. Technology and Business teams are faced with a challenge to architect and manage analytics platforms that extract optimum value from these event streams. Combining fast data with the advanced big data analytics through mining large volumes of historical data is increasingly becoming a key technology enabler for competitive differentiation and sustained economic value generation. Tapping into the value of data in real-time – the moment it arrives – is a significant opportunity but it requires the ability to track billions of events, generate real-time triggers from those billions of events reflecting the contextual usage and deviation in defined behavior, as well as to take right action at right time through the right channel instantaneously.
Building applications on streaming data has its challenges. If you’re a developer trying to use programs like Apache Spark or Storm to build apps, this webinar will explain the benefits and downfalls of each solution and how to choose the right tool for your next streaming data project.
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.