Videos (YouTube)

Data Modeling for Online Feature Store: An Example

In this video, Attila Toth, ScyllaDB Developer Advocate, shows you an example data model for an online feature store using ScyllaDB. See how you can design a scalable database schema that offers predi

Real-time ML with ScyllaDB as the Online Feature Store: Price Prediction Example

Attila Toth, Developer Advocate at ScyllaDB, introduces our latest feature store sample application: a used car price prediction app. Discover how ScyllaDB powers real-time machine learning apps by se

ScyllaDB Workload Prioritization Demo

ScyllaDB's Workload Prioritization lets you control how different workloads compete for system resources. It's used to prioritize urgent application requests that require immediate response times vers

ScyllaDB vs. DynamoDB: 5 Minute Demo

This demo compares ScyllaDB and DynamoDB in terms of elasticity, latency, and cost efficiency. It highlights how ScyllaDB scales faster, eliminates the need for external caching, avoids per-table capa

Demo: Predictable Performance at Scale to 2M OPS

This narrated demo shows ScyllaDB's linear scalability and low latency. It demonstrates real-time data ingestion and processing, maintaining single-digit millisecond P99 latencies even as capacity dou

Predictable Performance at Scale to 2M OPS

Watch this video to see how ScyllaDB delivers predictable performance at scale -- with single-digit ms latencies as we scale from 500K to 2M OPS in <10 minutes.

ScyllaDB vs Cassandra: 5 Minute Demo

This demo explores how ScyllaDB differs from Apache Cassandra in performance, elasticity, and capabilities such as workload prioritization. It shows how ScyllaDB shards data per CPU core, avoids garba

Inside Tripadvisor’s Real-time Personalization with ScyllaDB and AWS

What kind of traveler are you? Tripadvisor tries to assess this as soon as you engage with the site and offer you increasingly relevant information with every click—within a matter of milliseconds. Th

ScyllaDB Scaling in Action

See how ScyllaDB's Tablets architecture enables new levels of database elasticity.

ScyllaDB at 1M+ OPS

In this video, Attila Toth, ScyllaDB Developer Advocate demonstrates ScyllaDB Enterprise performing 1M+ ops/sec. Replicate the demo on your own cloud infrastructure: https://github.com/scylladb/1m-op

Exploring ScyllaDB's Architecture and Engineering Optimizations

Learn all about ScyllaDB's database internals, from the perspective of ScyllaDB Solution Architect Felipe Cardeneti Mendes. Chapters: 0:00 ScyllaDB internals with Felipe Mendes 07:51 Write Path - AP

Tutorial: Video Streaming Application built with NextJS

In this video tutorial Attila Toth, ScyllaDB developer advocate, walks you through a sample video streaming application built with ScyllaDB Cloud and NextJS.

Tutorial: Running ScyllaDB at 1M Operations per Second

What Makes ScyllaDB So Fast?

ScyllaDB is a monstrously fast and scalable distributed NoSQL database designed for high throughput and low latency at scale. But what makes ScyllaDB so fast?

Sizing Considerations for ScyllaDB

Get a overview of what matters most when building a cluster for your workload.

How Discord Migrated Trillions of Messages to ScyllaDB

🎥 Watch all the ScyllaDB Summit 2023 talks here: https://www.scylladb.com/scylladb-summit-2023/ Learn why and how Discord’s persistence team recently completed their most ambitious migration yet: mov

Understanding Storage I/O Under Load

sponsored by ScyllaDB Discover a new approach to exploring your disks and managing your IO workloads.

Indexes, Filters, and Other Animals

Scylla now supports a choice between Global and Local Secondary Indexes. Their performance characteristics will be widely different, and better or worse depending on the situation. Which will perform

What is ScyllaDB ?

ScyllaDB is the monstrously fast and scalable NoSQL database for data-intensive apps that require high performance and low latency.

Comcast Reduces P99 Latencies by 95% with ScyllaDB

How Comcast's move from Cassandra achieved a 10x improvement in latency, enabled them to handle 2x the requests at <5% of the cost and provided an extreme node reduction (962 to 78).