Name: Build an E-commerce Application with React, Spring Boot and NoSQL
Start: 2023-02-16T17:52:00Z
End: 2023-02-16T17:52:42.000Z
Location: BrightTALK
Rating: 4.7

DataStax is the real-time AI company. With DataStax, any enterprise can mobilize real-time data and quickly build smart, high-growth applications at unlimited scale, on any cloud. DataStax delivers the Astra DB cloud database built on Apache Cassandra® and the Astra Streaming event streaming technology built on Apache Pulsar.™

Are you struggling with the challenges posed by massive datasets and AI applications? Vector Search is a transformative solution that can help you address these issues. As a decision-maker, you always look for ways to optimize your organization's operations and maximize ROI. Luckily, integrating Vector Similarity Search into Cassandra can help you achieve these goals.

Join Patrick McFadin Apache Cassandra Committer and discover how: 

1. Vector Search can revolutionize handling AI workloads and managing large datasets.
2. Real-world applications of Vector Similarity Search in content-based image retrieval, recommender systems, and natural language processing.
3. Integrating Vector Similarity Search into Cassandra enables faster and more relevant data retrieval, boosting the performance of data-driven applications.
4. Vector Similarity Search in Cassandra can solve data management challenges, drive efficiencies, and maximize ROI for your organization.

Don't miss this opportunity to learn how the cutting-edge Vector Similarity Search functionality in Cassandra can solve your organization's data management challenges, drive efficiencies, and propel your business forward. This strategic move towards enhancing Cassandra's offering underscores its position at the forefront of scalable data management solutions and reaffirms its commitment to meeting the evolving needs of developers and businesses alike.

Vector Similarity Search in Apache Cassandra®

You have all this data coming into the system, what are you going to do with it? Maybe store it in some lake ‘o data to never be spoken of again? Or better yet, write it to a microservice’s dedicated store where no one has access to.

Let’s think about things in a different way - use that data in real time! Make decisions on the fly to help your customers with a better experience! Store the decisions as a record of business value already realized.

In this session, we are going to look at how streaming and real-time AI enables enterprises to do more with data. But we’re not going to weigh you down with all the boring business trends and percentages. We are going to review a working example of an ecommerce site watching the viewing trends of a live customer and promoting related items that are of strong interest to the person. It doesn’t get any more real time than this!

Real-Time AI Explained. Enabling Ecommerce Instant Decisions with Streaming

DataStax and Temporal are on a mission to help developers build durable, resilient apps that never fail, no matter how fast they scale or how demanding the business. But building reliable apps can be complex, creating obstacles and delays for developers working under intense pressure. 

Temporal and DataStax are delivering a new programming model for developers: cloud-native, invincible apps, without the burden of complexity, helping you focus on what you do best: building great software, fast.  Join us and hear:

- Temporal’s durable execution paradigm provides extreme reliability, and makes it trivial or unnecessary to implement distributed systems patterns like event-driven architecture, task queues, sagas, circuit breakers, and transactional outboxes.
- DataStax’s Astra platform provides the tools to build out real-time systems.
- Temporal and DataStax together provide a robust platform on which to build scalable, fault-tolerant applications.

We’ll also explore why Temporal chose Cassandra as the highly-reliable, scalable database for their own platform. And how this combination can deliver invincible apps for your business as well.

Building Invincible Applications with Temporal & Astra DB

Martin (Marty) Brodbeck joined Priceline as Chief Technology Officer in 2019. Marty is responsible for all product engineering, infrastructure, data and technology operations for Priceline.

At Priceline, Marty has spearheaded the company’s digital transformation, leading a product migration and instituting a new micro-services architecture powered by the cloud. Additionally, he developed a new data platform that powers the brand’s marketing and consumer capabilities, which have been essential to the growth of the company.

Driving Priceline's Digital Transformation with Real-Time Data

Ayushi Singh is a Senior Software Engineer in the Online Datastores team at Netflix. With her expertise in open-source projects like Apache Cassandra, Ayushi is helping drive Netflix's vision to entertain the world through scalable data solutions. Prior to her role at Netflix, Ayushi was a member of the Core Platform and Infrastructure team at PayPal implementing cloud platforms in a hybrid cloud setting. Her contributions empowered PayPal's business teams to scale their applications, serving millions of customers globally and processing billions of dollars in payments.

In this Digital Champions interview, Ayushi emphasizes the importance of creating an inclusive space for learning and collaboration in the technology industry, especially for women. Her insights are invaluable to fostering diversity in the field. Ayushi also discusses the power of Apache Cassandra and provides a glimpse into Netflix's strategic use of real-time data for content creation, infrastructure monitoring, and marketing strategies.

Ayushi Singh Provides a Glimpse of Netflix's Strategic Use of Real-Time Data

Are LLMs (Large Language Models) the most exciting new capability since the advent of mobile? 

ChatGPT has enterprises and developers racing to use LLMs to innovate products, customer service, marketing, and customer experiences.  

Watch this webinar to understand:

- Who should use LLMs
- How it will impact your enterprise
- How it relates to your real-time AI strategy
- How do LLMs relate to other AI and ML services and technology?

We explore the benefits of using LLMs for the enterprise, including the ability to provide real-time insights into customer behaviour and preferences, all while streamlining workflows and reducing costs. 

Uncover the relationship between LLMs and other AI and ML technologies, including their ability to process and analyze vast amounts of data in real-time. Additionally, we discuss the ethical considerations of LLMs, the potential for bias and the importance of transparency and accountability.

This webinar is ideal for enterprise leaders and decision-makers looking to stay ahead of the curve in the rapidly evolving world of AI and ML. Don't miss this opportunity to gain valuable insights into the power of LLMs for your enterprise AI strategy.

Large Language Models (LLMs) for the Enterprise" ChatGPT and Beyond

ACID transactions are coming to Apache Cassandra!  Tune in to learn how you'll be able to leverage Cassandra to apply a group of operations across several partition keys, and have it treated as an atomic, single unit of work.  See how this change is going to dramatically improve the Cassandra developer experience and open the Cassandra world up to a whole slew of new use cases.

We start by introducing the concept of ACID (Atomic, Consistent, Isolated, Durable) transactions within the Apache Cassandra paradigm.  We also discuss the current roadmap for implementation, as well as a little about the computer science behind the enhancement.

ACID Transactions on Cassandra

Looking even further forward into the next few years, how will you use Cassandra? The two areas of our community that will grow the fastest are cloud native and AI/ML workloads. Cassandra was built for the next generation of applications. We are adding even more capabilities to help you develop faster with less effort.

Cassandra Forward: Whats Next in Apache Cassandra Use Cases?

It’s time to bring the power of AI to your data. Join Matt Kennedy, Product Strategist and Dr. Charna Parkey, Real-time AI Product & Strategy Leader to learn:
- Why real-time AI is critical for market-leading apps
- How organizations can build AI-powered apps with proven success patterns
- How to prepare for real-time AI with event data
- And get a preview of how to bring ML to your real-time dataset

Unleash Real-time AI to your Event-based Data

Revital Kremer is leading the charge for ag-tech to help farmers overcome water scarcity as climate change continues to challenge growing conditions around the world. She joined SupPlant, a precision ag-tech company, after more than two decades working with technology teams in military, gaming, and other software domains.

SupPlant’s system gathers data from sensors placed on the plant trunk, on the fruit, and in the soil, collecting and transmitting measurements in real time. Learn how Revital and her team help farmers grow healthier plants through AI-powered irrigation, backed by real-time data

SupPlant Uses Real-Time Insights to Improve Water Usage and Crop Yields

In this video, hear insights from Eric Sammer CEO, Decodable and Ed Anuff CPO, DataStax on real-time data, streaming, and what it means for developers.

Decodable Makes Real-Time Data Simple

DataStax's CEO and Temporal's CTO discuss developer productivity and durable execution, how to build invincible apps with the right tech and partners, and advice for enterprises racing to become cloud-native.

Temporal Eliminates Complexities for Developers

What happened next? Bud partnered with DataStax to migrate to Astra DB on Google Cloud, meaning it has been able to massively scale globally. Bud is now operating on three continents, has just landed $80m in funding, and its product teams can drive growth by focusing on what they do best. 

Want to know how they pulled it off? Then join Michael Cullum of Bud and Orme de Saint Hilaire of DataStax as they tell the Reg’s Tim Phillips the story of how Bud boosted its growth, and how you can do the same. They will discuss:

- The problems of success when managing large amounts of data
- How DataStax Astra and GCP delivered a rapid scale-up
- What Bud learned from its implementation

Bud Use Case: Can serverless SaaS scale up your business?

Access to data has become a prerequisite for multiple business teams, placing greater strain on database architectures. Legacy systems that rely on a single server or access point can become overwhelmed and end up creating damaging bottlenecks that hinder operational efficiency. While investing greater resources may work as a temporary fix, this is unlikely to work long term; organizations need to redesign their approach to database infrastructure and build a system that can keep up with modern demands.

In this webinar from Datastax, Google Cloud and ESG, industry experts will spotlight the key issues plaguing traditional databases and discuss a new way to re-architect these infrastructures.

Tune in to hear more about:
— The impact of data explosion on traditional data management
— Why a managed services approach is so well suited to database workloads
— How Datastax and Google Cloud are working together to fuel customer success, through real case studies
— And much more

Real-Time All the Time: Redesigning Databases with DataStax & Google Cloud

Join us for a live interactive webinar and discover how the Real-Time Data Cloud will help you quickly deliver powerful modern applications and engaging digital experiences for your customers. You’ll hear:
 
Why real-time data provides advantages in navigating today's uncertain markets
How the new data architecture is unlocking real-time benefits, without the cost and complexity
How DataStax extended the power of real-time to every developer, beyond the once-required specialized skill set
The Real-Time Data Cloud is optimized for developers, deployed to any cloud and ready to support enterprise requirements for cost, security, governance and availability.

Real-Time Data Cloud: Build fast, scale without limits

DataStax is built on proven Apache Cassandra™ and the Stargate™ open source API platform. DataStax Astra is the new stack for modern data apps as-a-service, built on the scale-out, cloud-native, open source K8ssandra™.

A Day in your Life with Cassandra

Winning enterprises take data, process it, and use it to quickly deliver an instantaneous experience to customers. In this video, hear insights from our Chairman & CEO Chet Kapoor on real-time data, what it means, and why now is the time to activate it in every application and for all of your customers.

Find out why real-time data has a critical role in:
- Improving the customer experience
- Driving operational processes
- Gaining a competitive advantage as a data-driven enterprise

Why Real-Time Data Matters Now

In this session, we’ll show you how to build a simple e-commerce site using Astra DB, Spring Boot, and Astra Streaming. This particular workshop will focus on checkout and order processing, as we build the system which streams our order data to different parts of the “business.” We’ll also have web-side components to allow customers to view the current progress of their order.Session Details:
- Setting up your Astra DB
- Learn how to design high performance Cassandra data models
- Learn how to build checkout and order processing features

Build an E-commerce Application with React, Spring Boot and NoSQL

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Build an E-commerce Application with React, Spring Boot and NoSQL

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