NoSQL and ScyllaDB Overview

We’re at the intro, and I’m going to start by talking about “NoSQL” in general. So what we see here is the cap theorem. The cap theorem states that distributed databases or NoSQL databases have three characteristics or attributes that we would like to strive for, and they are availability, consistency and partition tolerance. However, the cap theorem states that there is a trade-off between these three attributes, and we have to choose two out of those three so we can’t have it all, and maybe a few words about each one and what does it mean. So availability means that we will still be able to serve requests and remain highly available even if there is some kind of failure, say, hardware failure, or for any other reason some of our nodes in the distribute the database become unavailable. Consistency, there are different ways to define consistency, but one that I like and it’s simple is that for the latest for a read request, we would always get the latest write. So our data is consistent, and partition tolerance means that because we are talking about the distributed database, even if there is a network failure or for whatever reason some of our nodes become unavailable, the system would still work and would still be serving requests. So I placed on this slide some databases, these are just examples. There are hundreds of databases. So you can see that, for example, Apache HBase and MongoDB prefer consistency and partition tolerance while ScyllaDB as well as Apache. Cassandra and Amazon DynamoDB give a preference for availability and partition tolerance over consistency. Now that doesn’t mean that they’re not consistent and I’m going to talk about that in just a minute. Okay, another way to look at NoSQL databases is according to their data model, so there are a few different data models that are used. This is one way to classify them according to the complexity, starting from the least complex. So a key value/store means that we have simply a key and a value. It’s very simple. Some examples are Redis and Aerospike. Of course, there are others. Next, a bit more complex would be documents store. And here we have our data model that’s more structured. Think about JSON or XML or some other structured document. And some examples here are MongoDB and Couchbase. Next, we have a more complex data model, which is wide column store. And you can actually think about the data model as a table with rows and columns. And here we have ScyllaDB together with Apache Cassandra and some others. And finally, the most complex would be a graph data model where we have our data modeled as edges and vertices. So that’s a graph database. And some examples are JanusGraph and neo4j. And by the way, JanusGraph can work with ScyllaDB as the underlying data storage. Great. So I talked about NoSQL in general. Let’s talk about ScyllaDB specifically some of the attributes of ScyllaDB. So high availability,. I mentioned ScyllaDB is built to remain highly available even if there are some failures or disasters. This is done by replicating data. So for each piece of data that we store, we have multiple copies and I’ll show you how that works in just a bit. And that’s also something that can be configured by the user according to the specific use case. Highly scalable, so, ScyllaDB is easy to scale by adding more nodes. A cluster, again, this is a distributed database. So it works on multiple nodes and the system scales by adding more nodes. Let’s take for example, say we’re an e-commerce website and Black Friday is coming up. We know we’re going to have more traffic so we can simply add more nodes before Black Friday. We can do that without any downtime as the system is running. Add more nodes, be able to serve more requests on Black Friday, and then maybe after Black Friday we can scale back down again, removing nodes without any downtime. Performance, so there was a question in the lounge before we started about ScyllaDB sweet spot. So one of the things that comes to mind is applications that require high performance. We’re talking about very low latencies below 10 milliseconds and very high throughput. So if your application requires high performance, then ScyllaDB is probably a good candidate. Low maintenance, so ScyllaDB is built with autonomous capabilities, auto tuning, and it typically also requires less nodes to run than other databases, which also makes it easier to maintain. And last but not least, very importantly, ScyllaDB is a drop in replacement for Apache Cassandra and for Amazon DynamoDB. Meaning that if you have your application running with either of these two databases, you can pretty much keep your application as it is and switch your end point configuration for your application to run with ScyllaDB instead. And by doing that, you get quite a lot of benefits that you see here, better performance, easier to maintain. And when talking about DynamoDB, also you avoid vendor lock in. So ScyllaDB can run on different clouds on prem and so on.