In practical terms, how do you begin to plan your ultra-efficient Scylla topology? The shift can be intimidating for those coming from a background in Cassandra, or for those coming from a primary-replica architecture, or from a plain old monolithic database implementation. In this post we’ll layout a checklist for designing a Scylla cluster that incorporates both horizontal and vertical scaling.
I recently had the pleasure of exchanging a few questions and answers with Guy Shtub, Manager of Scylla University. Guy had some exciting news about a new module available for Scylla University users plus shared his insights into what else is in the works.
We’ve written a pretty comprehensive blog about migrating to Scylla in general, but not all of those migration strategies apply to a managed cloud solution. So let’s drill down into specifics and step-by-step instructions targeted directly to your Scylla Cloud success.
We recently launched Scylla Cloud, allowing you to get the most out of Scylla while not having to burden yourself with cluster management tasks. In this blog post we will cover the initial onboarding process, including creating an account and spinning up a cluster.
Scylla’s March 2019 webinar on database migration drew broad interest and will likely remain a popular topic for years to come. So, you’ve decided to adopt Scylla (or Cassandra). What’s the best way to get your Big Data uploaded into your new cluster? What strategies, tools and techniques can you use to get your terabytes or petabytes from point A to point B? Those were the questions of the day for Dan Yasny, Field Engineer of ScyllaDB.
If you are a Scylla user, you must be familiar by now with Scylla Monitoring Stack (downloadable for free from Github) which is the recommended way to monitor Scylla. We just released Scylla Monitoring Stack version 2.2. There are a few configuration simplifications you should be aware of and there is an exciting new dashboard for CQL optimization we hope you’ll find useful. CQL Optimization Dashboard The new CQL Optimization Dashboard is a tool to help identify potential issues with queries, data model and driver. The concept of the dashboard was introduced in Scylla Summit 2018. If you missed it, […]
Another week, another Spark and Scylla post! This time, we’re back again with the Scylla Spark Migrator; we’ll take a short tour through its innards to see how it is implemented. Read why we implemented the Scylla Spark Migrator in this blog. Overview When developing the Migrator, we had several design goals in mind. First, the Migrator should be highly efficient in terms of resource usage. Resource efficiency in the land of Spark applications usually translates to avoiding data shuffles between nodes. Data shuffles are destructive to Spark’s performance, as they incur more I/O costs. Moreover, shuffles usually get slower […]
So you’re thinking of running your applications with Scylla? You’ve probably heard it’s a lightning fast, self-optimizing, highly available Apache Cassandra drop-in replacement. Yet you may still have questions like: How do I upgrade from my current system? How many nodes do I need? How do I ensure that my data is consistent across the database? How should applications be written to maximize database performance? How do I scale up or scale out? To make it easier to find answers to these questions and many more, we have launched Scylla University. Anyone in your organization can now take advantage of […]
We needed a Python interpreter that can be shipped everywhere. You won’t believe what happened next! “When I said I wanted portable Python, this is NOT what I meant!” In theory, Python is a portable language. You can write your script locally and distribute it to other machines with the Python interpreter. In practice, things can go wrong for a variety of reasons. The first and simpler problem is the module system: for a script to run, all of the modules it uses must be installed. For Python-savvy users, installing them is not a problem. But for a software vendor […]
Spark Structured Streaming with Scylla Hello again! Following up on our previous post on saving data to Scylla, this time, we’ll discuss using Spark Structured Streaming with Scylla and see how streaming workloads can be written in to ScyllaDB. This is the fourth part of our four part series. Make sure you check out all the prior blogs! Our code samples repository for this post contains an example project along with a docker-compose.yaml file with the necessary infrastructure for running the it. We’re going to use the infrastructure to run the code samples throughout the post and run the project itself, […]