Webinar: Dyn + DataStax - helping companies deliver exceptional end-user experience

The document outlines a training program from DataStax on Apache Cassandra, including an introduction to various courses that cover topics such as core concepts, operations and performance tuning, building scalable Java applications, and data modeling. It provides details on the objectives, length, audience, prerequisites, and agenda for each course. The document also includes a schedule of public course dates and locations for attendees to sign up for training.

Why you need benchmarks Finding the right database solution for your use case can be an arduous journey. The database deployment touches aspects of throughput performance, latency control, high availability and data resilience. You will need to decide on the infrastructure to use: Cloud, on-premise or a hybrid solution. Data models also have an impact on finding the right fit for the use case. Once you establish a requirements set, the next step is to test your use case against the databases of choice. In this workshop, we will discuss the different data points you need to collect in order to get the most realistic testing environment. We will cover: Data model impact on performance and latency Client behavior related to database capabilities Failover and high availability testing Hardware selection and cluster configuration impact We will show 2 benchmarking tools you can use to test and benchmark your clusters to identify the optimal deployment scenario for your use case. Attend this virtual workshop if you are: Looking to minimize the cost of your database deployment Making a database decision based on performance and scale data Planning to emulate your workload on a pre-production system where you can test, fail fast and learn.

mParticle processes 50 billion monthly messages and needed a data store that provides full availability and performance. They previously used Cassandra but faced issues with high latency, complicated tuning, and backlogs of up to 20 hours. They tested Scylla and found it provided significantly lower latency and compaction backlogs with minimal tuning needed. Scylla also offered knowledgeable support. mParticle migrated their data from Cassandra to Scylla, which immediately kept up with their data loads with little to no backlog.

We recently launched DataStax Enterprise 4.5 - the fastest, most scalable distributed database technology with blazing performance, 100x faster analytics and automated diagnostics. Join DataStax’s product gurus Martin Van Ryswyk, EVP of Engineering, and Robin Schumacher, VP of Products, in an open dialog as they discuss the importance of - - Selecting the right database technology for today’s digital world - Integrated analytics for lightning fast customer interactions - Merging operational and historical data for the most accurate insights, possible

DataStax recently announced the general availability of DataStax Enterprise 4.7 (DSE 4.7), the leading database platform purpose-built for the performance and availability demands of web, mobile, and IOT applications. In this product launch webinar, Robin Schumacher, VP of Products, explores the wide range of enhancements in DSE 4.7 including enterprise class search, analytics, and in-memory.

Big data doesn't mean big money. In fact, choosing a NoSQL solution will almost certainly save your business money, in terms of hardware, licensing, and total cost of ownership. What's more, choosing the correct technology for your use case will almost certainly increase your top line as well. Big words, right? We'll back them up with customer case studies and lots of details. This webinar will give you the basics for growing your business in a profitable way. What's the use of growing your top line but outspending any gains on cumbersome, ineffective, outdated IT? We'll take you through the specific use cases and business models that are the best fit for NoSQL solutions. By the way, no prior knowledge is required. If you don't even know what RDBMS or NoSQL stand for, you are in the right place. Get your questions answered, and get your business on the right track to meeting your customers' needs in today's data environment.

Disney+ Hotstar is the fastest growing branch of Disney+. Join Disney+ Hotstar Architect Vamsi Subhash and senior data engineer Balakrishnan Kaliyamoorthy to learn… How Disney+ Hotstar architected their systems to handle massive data loads Why they chose to replace both Redis and Elasticsearch Their requirements for massively scalable data infrastructure and evolving data models How they migrated their data to Scylla Cloud, ScyllaDB’s fully managed NoSQL database-as-a-service, without suffering downtime

We will present our O365 use case scenarios, why we chose Cassandra + Spark, and walk through the architecture we chose for running DataStax Enterprise on azure.

Data security is an absolute requirement for any organization – large or small – that handles debit, credit and pre-paid cards. But navigating, understanding and complying with PCI-DSS (Payment Card Industry – Data Security Standards) regulations can be tough. In this webinar, we’ll examine the guidelines for securing payment card data and show you how a combined solution from DataStax and Gazzang can put you on course for compliance.

We will start from understanding how Real-Time Analytics can be implemented on Enterprise Level Infrastructure and will go to details and discover how different cases of business intelligence be used in real-time on streaming data. We will cover different Stream Data Processing Architectures and discus their benefits and disadvantages. I'll show with live demos how to build Fast Data Platform in Azure Cloud using open source projects: Apache Kafka, Apache Cassandra, Mesos. Also I'll show examples and code from real projects.

AdTech requires high speed at massive scale. Sizmek serves millions of requests every second. Requests need to be processed in tens of milliseconds, while involving 10 simultaneous lookups into a database that contains tens of billions of profiles. In this presentation, you will discover how Scylla enables Sizmek’s real-time bidders to query a gigantic user profile store quickly and reliably with only a few nodes. We’ll discuss data modeling, server and driver configuration, techniques to minimize disk access, as well as considerations for leveraging Spark while migrating from HBase.

We have seen rapid adoption of C* at eBay in past two years. We have made tremendous efforts to integrate C* into existing database platforms, including Oracle, MySQL, Postgres, MongoDB, XMP etc.. We also scale C* to meet business requirement and encountered technical challenges you only see at eBay scale, 100TB data on hundreds of nodes. We will share our experience of deployment automation, managing, monitoring, reporting for both Apache Cassandra and DataStax enterprise.

This session will address Cassandra's tunable consistency model and cover how developers and companies should adopt a more Optimistic Software Design model.

Businesses that once measured performance in seconds now measure it down to the millisecond and even the microsecond in order to provide optimal user experience. For a NoSQL database few things are more important than keeping latencies low and bounded. Yet some databases suffer latency spikes from such regular occurrences as Java Virtual Machine (JVM) “garbage collection,” context switches, database repair, cache flushes and so on. This makes long-tail latency very tricky to diagnose and fix, as it’s often a “whack-a-mole” exercise. In this session, we will cover: The systemic causes of latency spikes How to keep latencies bounded and predictable How to manage latency-inducing events How Scylla helps optimize for 99% latency of <1msec

Looking to strengthen your expertise of Cassandra and DataStax Enterprise? This DataStax Training Webinar provides an overview of what you need to get the most out of Cassandra and your DataStax Enterprise environment. Whether you’re a developer or administrator, novice or a Cassandra expert, there is a class that will meet your experience level and needs.

This document discusses building data pipelines for both static and streaming data using Apache Spark and DataStax Enterprise (DSE). For static data, it recommends using optimized data storage formats, distributed and scalable technologies like Spark, interactive analysis tools like notebooks, and DSE for persistent storage. For streaming data, it recommends using scalable distributed technologies, Kafka to decouple producers and consumers, and DSE for real-time analytics and persistent storage across datacenters.

The document discusses best practices for moving Cassandra pilots and proofs of concept (PoCs) to production. It recommends starting with defining queries, building out 5-8 pilots, and designing REST APIs first. When moving to production, considerations include infrastructure, testing, coding practices like using asynchronous execution, data modeling for queries and analytics, and application optimization techniques.

As new types of data sources emerge from cloud, mobile devices, social media and machine sensor devices, traditional databases hit the ceiling due to today’s dynamic, data-volume driven business culture. Join us in this online webinar and learn how you can incorporate a modern, NoSQL platform into daily operations to optimize and simplify data performance. DataStax recently announced DataStax Enterprise 4.0, a production-certified version of Apache Cassandra with an in-memory option, enterprise search, advanced security features and visual management tools. Give your developers a simple and powerful way to deliver the information your customers care about most—unconstrained by the complexities and high costs of traditional database systems. Learn how to: - Easily assign data based on its performance needs on traditional spinning disk, SSD or in-memory. All in the same database instance - Leverage DataStax’s built-in enhancements for broader information search and analysis even with many thousands of concurrent requests - Visually monitor, manage, and fine-tune your environment to get the most of your online data

In today’s environment, you must serve your customers with uptime (all the time) availability, plus hidden benefits like state-of-the-art fraud detection and game-changing recommendation engines. In this webinar, you’ll learn how to: -Get uptime, all the time, so you can serve your customers without outages -Ingest huge velocities of data from anywhere -Maximize mobile, online and cloud applications with the security your customers expect -Identify patterns between formerly silo’d data, even text and call logs -Get the search & insight you need without performance hits

The definition of eCommerce has totally changed, expanding from a purely retail perspective to mean "the place where your customers meet you online." Whether you offer mortgage services or catering recommendations, you must think of your online transaction application as an eCommerce site.

Cassandra is a distributed, massively scalable, fault tolerant, columnar data store, and if you need the ability to make fast writes, the only thing faster than Cassandra is /dev/null! In this fast-paced presentation, we'll briefly describe big data, and the area of big data that Cassandra is designed to fill. We will cover Cassandra's unique, every-node-the-same architecture. We will reveal Cassandra's internal data structure and explain just why Cassandra is so darned fast. Finally, we'll wrap up with a discussion of data modeling using the new standard protocol: CQL (Cassandra Query Language).

The design of Apache Cassandra allows applications to provide constant uptime. Peer-to-Peer technology ensures there are no single points of failure, and the Consistency guarantees allow applications to function correctly while some nodes are down. There is also a wealth of information provided by the JMX API and the system log. All of this means that when things go wrong you have the time, information and platform to resolve them without downtime. This presentation will cover some of the common, and not so common, performance issues, failures and management tasks observed in running clusters. Aaron will discuss how to gather information and how to act on it. Operators, Developers and Managers will all benefit from this exposition of Cassandra in the wild.

In online residential and commercial real estate, even fractions of seconds in response times affect customer satisfaction and conversion to revenue. The need for continuous availability is paramount to deliver the levels of service customers demand from modern online applications. Join David Prinzing, Enterprise Architect at Clear Capital to discover why Clear Capital, a premium provider of real estate asset valuation and collateral risk assessment, chose DataStax as the database-backbone for their ClearCollateral Platform. David will discuss how DataStax Enterprise, the world’s fastest, most scalable distributed database technology built on Apache Cassandra ensures 100% uptime for over 122 million properties (90% of all the properties in the United States) and supports reporting on over 1 Billion total valuations while never going down. - The challenges in building real-time applications using relational technologies is forcing financial services firms to migrate to distributed database technologies - How Clear Capital delivers 100% availability and real-time decision support across multiple data centers in the Amazon Cloud using DataStax Enterprise - Why Apache Cassandra’s architecture delivers always-on, customer engaging applications that capture new business opportunities

This webinar follows the process of evaluating different big data platforms based on varying use cases and business requirements, and explains how big data professionals can choose the right technology to transform their business. During this session, Ooyala CTO, Sean Knapp will discuss why Ooyala selected DataStax as the big data platform powering their business, and how they provide real-time video analytics that help media companies create deeply personalized viewing experiences for more than 1/4 of all Internet video viewers each month.