DataStax Accelerate On-Demand

Explore the trends, strategies, and technologies driving application modernization and data management that will help you move your business into the future. Learn about the future of Apache Cassandra™, DataStax Constellation, a cloud-native data platform, and 70+ technical sessions designed to help you build game-changing applications in the cloud, on premises, or in a hybrid cloud environment.

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Modern Data Architectures with Kafka and Cassandra

Learn how modern enterprises are building their event-driven architectures to take advantage of stream processing paradigms to source data from microservices, databases, IoT events, and other critical systems while enriching it and making it available to answer real-time questions core to becoming a digital enterprise. Architectural patterns will be the core of this talk along with discussion on why Kafka and Cassandra should be best friends as core components of any modern data architecture.

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Introducing DataStax AppStax: Making the Database Obsolete

Imagine a world in which you don’t have to worry about your database. A world where physical data modeling, query optimization, denormalization, ORMs, drivers, migrations, and all those other database headaches are relics of an unproductive past. Imagine a world in which your data layer empowers you to build applications quicker and better and you can prototype a data backend in minutes as well as easily evolve your application’s data model in production. Imagine a world in which database administration is a thing of the past. A world where you can scale with the push of a button and no downtime. In this session, we’ll discuss how we can make that world a reality. We’ll provide a technical preview of a fully managed and highly intelligent database solution that gives you all the power and agility of a modern database without any of the headaches. Whether you are trying to build a new application, transition to a microservices architecture, or move workloads off a mainframe or legacy database, this new solution can get you there faster, cheaper, and with complete peace of mind.

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Data Modeling Is Dead… Long Live Schema Design!

When it comes to managing data for modern, agile environments, is data modeling a roadblock? Or is it in fact one of the keys to achieving agility? If traditional data modeling will no longer support what businesses need today, what are the alternatives? A distorted perception nowadays is that data modeling has become a bottleneck and doesn't fit in an agile development approach. You may pretend that it is not happening. Or blame complexity, speed of change, culture, or developers’ mentality. Or argue that data modeling is actually agile. The reality is that Data Modeling needs to be re-invented in order to remain relevant. In this session, we will look at some key enablers of agile data modeling, including Domain-Driven Design and physical schema design for Cassandra and DSE.

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Data as a Service: Transforming Enterprise Data into Modern Applications

Keith develops strong lasting relationships at CTO Boost. He makes every client his priority, whether it is a start-up, non profit or multinational corporation, Keith treats his connections with special attention and tailored approach.​ A highly experienced professional in sales and marketing, Keith’s expertise covers data and cloud computing strategy, AI, blockchain, AR/VR, ML and NLP.

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Cassandra’s Got Go for Vue Mobility!

Go is an open source programming language that makes it easy to build simple, reliable, and efficient software. Vue.js is a progressive and lightweight framework for building user interfaces. Both of these technologies grow in popularity every day. And compared to other monolithic languages or frameworks, are designed to be incrementally adoptable amongst developers. In this presentation, Adron Hall and Cristina Veale will talk about these two technologies and how they integrate with Apache Cassandra and DataStax Enterprise. They’ll show you how Go and Vue.js—when paired together—make a powerful, yet elegant, solution for your development needs. Key takeaways include: Delving into patterns and practices Discuss disparate IDEs like VS Code and JetBrains GoLand Utilizing DataStax Academy Twitch to stream our development progress

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Rapid Cloud Development with Spring Boot and Cassandra

Development today is all about getting your apps into the hands of your customers as quick as possible. It is also about keeping your data close to the customer so that the applications are more responsive. Consequently, developers are asked to do more with less resources. Enter into the picture the powerhouse combination of Spring Boot and Apache Cassandra™. Both of these technologies are best of class, with the cloud and global distribution at the heart. Spring Boot brings rapid development of cloud-native applications to the table, which can get a developer from start to production in minutes. Cassandra brings a true active-active globally distributable data store to the party that brings the data to the app, both of which can be close to the customer in a cloud world. In this talk we will look at Cassandra deployed in the cloud and then walk through the rapid development of Spring Boot applications backed with cloud-deployed Cassandra as a distributed data store to build true cloud-native applications built for global delivery.

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Creating a Python Microservice Tier in Four Sprints with Cassandra, Kafka, and DSE Graph

Join Jeff Carpenter, DataStax Director of Developer Advocacy, as he retraces his journey to create a Python implementation of the KillrVideo microservice tier in four sprints.  In this talk we’ll consider: Advice on API design and infrastructure selection for microservice architectures The case for Python as a viable language for microservice implementations Best practices for integrating Apache Cassandra, Apache Kafka, and DataStax Enterprise Graph in Python applications Lessons learned from livestreaming a graph recommendation engine implementation on Twitch

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Designing for Time Series Applications at Scale with DataStax Enterprise

Time series data sets are everywhere—and handling them poses many challenges. Large volumes of data need to be stored over long periods of time and retrieved efficiently, and downtime is not an option. In this talk, we will explore how Apache Cassandra and DataStax Enterprise (DSE) have built-in features, such as DSE File System, Search, and Analytics, that can be used to design robust solutions at scale for time series use cases.

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Building a Feature Store and Experiments Platform with DataStax Enterprise at Condé Nast

The Feature Store is a centralized, curated repository for machine learning features of our content and users. The Experiments Platform provides multivariate testing capabilities across our brands. These services deliver very low latency and high availability SLAs under heavy load. Learn about the challenges, pitfalls, and successes we experienced building these services and how we’re leveraging DataStax Enterprise.

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Speed Up Your Apache Cassandra™ Applications: A Practical Guide to Reactive Programming

We have all introduced more or less functional programming and asynchronous operations into our applications in order to speed up and distribute treatments (e.g., multi-threading, future, completableFuture, etc.). To build truly non-blocking components, optimize resource usage, and avoid "callback hell" you have to think reactive—everything is an event. From the frontend UI to database communications, it’s now possible to develop Java applications as fully reactive with frameworks like Spring WebFlux and Reactor. With high throughput and tunable consistency, applications built on top of Apache Cassandra™ fit perfectly within this pattern. DataStax has been developing Apache Cassandra drivers for years, and in the latest version of the enterprise driver we introduced reactive programming. During this session we will migrate, step by step, a vanilla CRUD Java service (SpringBoot / SpringMVC) into reactive with both code review and live coding. Bring home a working project!

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Serverless and Microservices: Time for a New Data Model?

Another day, another application development methodology. Serverless functions are the new rage. With them, everything becomes a microservice. You’ve already got enough on your mind just trying to figure out where serverless functions and microservices fit into your architecture, when it hits you—"what effect is this going to have my data?" Great question! Let’s spend some time walking through the different application deployment methodologies and what to consider when designing your data model.

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