This paper outlines 7 key considerations that help teams tap the many benefits a DBaaS has to offer — without falling into some of the common traps.
An online travel booking company, Kiwi.com, experienced a worst-case scenario: a catastrophic fire in a datacenter running their customer-facing services. Learn how Kiwi survived, thanks to a well-planned high availability architecture, supported by the appropriate technologies.
This paper covers the tradeoffs between availability and consistency, the architectural differences between NoSQL and NewSQL plus see the YCSB benchmark results for ScyllaDB & CockroachDB.
When and how to migrate data from SQL to NoSQL are matters of much debate. It can certainly be a daunting task, but when your SQL systems hit architectural limits or your cloud provider expenses skyrocket, it’s probably time to consider a move.
Learn common approaches to caching data, seven reasons why external caching can be a bad choice, how ScyllaDB’s embedded cache isolates developers from cache-specific code and delivers greater reliability, better performance, and lower TCO, plus get real-world examples of successfully eliminating external cache by companies such as Comcast.
Many companies have migrated from DataStax Enterprise to ScyllaDB over the last few years. In doing so, these companies have realized faster, more consistent performance for their mission-critical applications, saved millions in infrastructure and licensing costs, and freed up countless hours previously spent tuning their systems in attempts to get desired levels of performance. Read to get a breakdown of ScyllaDB’s advantages
ScyllaDB delivers the most scalable, fastest and most reliable NoSQL database as a managed service. This paper provides an overview of ScyllaDB Cloud and explains the underlying technology that makes ScyllaDB not only more performant than other DBaaS options but also much more cost-effective.
While scaling out the database is the norm for Big Data systems, there are many hidden costs and complexities associated with “node sprawl” that can be remedied by instead deploying smaller clusters of larger database nodes. This paper explores the merits of small clusters and shares test results that debunk the concerns some organizations have about using large nodes.
In this paper we explain the key design decisions that went into building a drop-in replacement for Apache Cassandra or Amazon DynamoDB with scale-up performance of 1,000,000 IOPS per node, scale-out to hundreds of nodes and 99% latency of less than 1 millisecond. Accomplishing this called for rethinking many of the foundational architectural choices behind other NoSQL databases.
ScyllaDB was architected and implemented by engineers with deep-level knowledge of operating systems and distributed systems, complemented by an appreciation for the power of control theory. A foundational architectural principle, self-optimizing capabilities manifest themselves in every aspect of the ScyllaDB database.
In this paper, we compare ScyllaDB with Amazon DynamoDB. We’ll cover the detailed methodology of our testing before demonstrating that ScyllaDB performs significantly better than Amazon DynamoDB under real-world conditions. Our evaluation also demonstrates that ScyllaDB delivers significant cost savings over Amazon DynamoDB.
Over-eager ingestion can result in a buildup of queues of background writes, possibly to the point of depleting available memory.This paper explains how ScyllaDB ensures that ingestion of data proceeds as quickly as possible, but not quicker.