The era of Big Data is here, and with it the enormous challenge of scaling the database to support Big Data applications. Sharding costs millions and saddles your teams with permanent, debilitating complexity that adds cost, risk, and time to everything. There is a different way. Join us for this free webinar, and gain invaluable insight into the latest trends and customer-proven solutions for scaling Big Data applications. Insight that you can put into action at your company today!Read more >
Recent years have seen an explosion in the number of different platforms and approaches used to store, process and analyze data in multiple formats from multiple sources. An abundance of data platforms (relational and non-relational databases, NoSQL, NewSQL, Hadoop, database as a service, etc.) has created a complex data management landscape that relies on the integration of multiple interdependent platforms and analysis tools. This trend is expected to continue in 2017. This webinar will preview how the database market is expected to change and what database professionals can do to use these changes to their advantage.
In this session you’ll:
- Learn what’s driving increasing adoption trends in specific data platforms like NoSQL and Hadoop
- See how cloud-based data platforms are being used—and who is using them
- Discover the implications of IoT for data platforms
- See a demo of a new database management platform designed to address these changes
In this presentation, we will discuss scaling choices to Big Data, your options, decision points, and how to use existing infrastructure. Traditional relational databases like Oracle and IBM have been the de facto RDBMSs for decades. They do many things very well and are still a strong choice for high performance transactional systems, especially for data volumes below a few terabytes. However, when data volumes begin to scale, many enterprises are looking for more cost-effective alternatives.
Distributed computing (i.e., the ability to scale out on commodity hardware) is a disruptive technology underpinning the new wave of database innovators such as SQL-on-Hadoop, NoSQL and NewSQL solutions. These solutions can offer a dramatic price/performance improvement over legacy databases. Incumbent database vendors have faced threats to their dominance in the past, but it is different this time, because of the volume, velocity, and variety of data growth.
In this presentation we will cover an overview of the Big Data landscape with a focus on scale out architectures.
Toshiba's GridDB is an open source specialized data store purpose-built for handling enormous amounts of data generated by the Internet of Things (IoT). GridDB offers in-memory processing to boost performance, time-series functionalities for IoT data, excellent scale-out on commodity hardware for increasing data needs and great reliability for mission-critical applications.
Toshiba has been building large scale IoT projects even before IoT was known as IoT. GridDB was conceived at Toshiba in 2013 to solve growing data needs and time-series data related problems that its customers faced. Since 2014 Toshiba’s customers in Japan spanning industries such as utilities, manufacturing, building management etc. have been harnessing the power of GridDB.
Join us to know more about:
1. Properties of IoT data and database requirements for handling it
2. Overview of GridDB
3. Technical details of GridDB including data models, performance, scalability, and reliability
4. Real world IoT use cases powered by GridDB
5. Programming Demo - modeling sample Wind Mill farm data using GridDB
The ability to collect and analyze up-to-the minute data can provide businesses a competitive edge. From applications developed for online merchandising to those that save human lives or help gaming companies create the next big blockbuster, collecting and analyzing extensive incoming data with speed provides you with the intelligence to make the right decisions and act on those decisions in real time.
During this live event Matt Aslett, Research Director at 451 Research will dig deeper into the advantages of real-time analytics. Matt will examine today’s complex database ecosystem and provide insights into technologies that can deliver on the true promise of real-time analytics.
During this event you will learn:
-The impact of new technologies such as Hadoop and NewSQL on real-time analytics
-Differences between using transactional databases vs. interactive data warehousing for analytics
-Core technologies that enable real-time analytics