RedisDays London 2022 Overview

RedisDays, our three-part worldwide virtual event kicked off with a stop in London this year, where our Redis experts and esteemed guests dug deep into the power of sub-millisecond speed. 

RedisDays is an opportunity to share with our community all the learnings and technical strides we’ve made in the past year, with new product announcements, best practices, and new customer use cases for real-time data. Below are some of the highlights from RedisDays London 2022.

Keynote: The Age of Real-Time is Now. Accelerate or Get Disrupted

Ofer Bengal, Redis Co-Founder and CEO, kicked things off with a keynote speech that boils down to one core idea: Many people use real-time data without noticing it. Real-time data is the technical backbone of modern living, with use cases that extend to manufacturing, airline, hospitality, telecommunications, healthcare, online advertising, cybersecurity, gaming, digital mobility, shipping services, social media, among many others. 

Besides highlighting how real-time data at scale is used daily to improve customer experience in many applications and touch points, here are the key takeaways and product announcements from London’s keynote:

• JSON is now generally available and provides a flexible and high-performance document store with native indexing and full-text search.

• RedisFI demo showcases how to develop a Financial Services RoboAdvisor real-time app with JSON and Search and Query.

• Redis’ popularity is reflected by the 5M+ Redis containers launched daily on DockerHub, more than MongoDB, Elastic, and Cassandra combined.

• Redis addresses many issues while providing sub-millisecond latency even while processing millions of operations per second.

• Your real-time data stack should support all data models and processing engines.

Click here to register and view the keynote on-demand.

Accelerate Your Apps with the Real-Time JSON Document Store from Redis

In this session, Ash Sahu, Sr. Director of Product Marketing, and Pieter Cailliau, Director of Product Management at Redis, focused on the real-time JSON document store. This presentation addressed how many types of data, including JSON, are needed for modern digital applications, but are restricted by rigid schemas of relational database management systems (RDBMS) and the slow performance of disk-based document databases.

Here are some noteworthy highlights from this presentation:

• JSON, now generally available, is designed for the flexible and high-performance requirements of modern document stores.
  
• JSON, supports atomic operations, native indexing query, full-text search, flexible deployment options, on-premise or as a managed service in the cloud.
  
• Mixed workloads performance test shows up to 50X more throughput than MongoDB and 7X more than Elasticsearch.

Want to learn more? Watch the session in its entirety by registering here.

Best Practices to Modernize Your Data Architecture

This session, led by David Loshin, President of Knowledge Integrity Inc., and Henry Tam, Sr. Solutions Marketing Manager at Redis, showcased best practices for modernizing data architectures still hampered by legacy technologies.

So what were the key takeaways from this session? Here they are at a glance:

• The financial services industry is facing growth challenges that impact their customer experience, risk and compliance, reporting, and ability to identify new business opportunities. 

• Aging legacy systems impede competitiveness with digital native fintech disruptors.

• Many customers are deploying Redis Enterprise to modernize their legacy applications to support real-time use cases, including customer360, granular access management, and fraud management

Missed the session? Watch it here.

Real-Time Data Pipelines: NLP + Redis

RedisDays London wrapped up with a fireside chat between Allen Terleto, Field CTO at Redis, and Alexander Mikhalev, AI/ML Architect at Nationwide Building Society, who discussed building real-time natural language processing (NLP) data pipelines using Redis to transform financial services processes. 

Here are some of the main points addressed during this one-on-one conversation:

• NLP helps to analyze and understand free-form and unstructured text.  

• Use cases include the summation of large amounts of text and Q&A chatbots.

• NLP requires the performance and scalability of an in-memory data layer like Redis.

Interested in learning more about NLP data pipelines? Take notes by watching on-demand.