In this webinar, SingleStore Product Manager Jacky Liang took a live audience through the process of building an analytics app in just a few minutes. You can view the webinar and download the slides here.
In just a few minutes in the middle of the webinar, Jacky created a free SingleStore account; installed SingleStore on AWS; loaded in some data; and created a dashboard using Looker, a popular analytics tool.
Jacky also explained some SingleStore basics and gave a quick overview of SingleStore’s architecture. We encourage you to read about the details here, then view the webinar to see SingleStore in action.
SingleStore Now Free to Use
It’s already widely known that SingleStore is a highly capable database. What’s not so widely known is that SingleStore is now free to use, up to 128GB of RAM usage. Because SingleStore is memory-led, not memory-only, the actual database size supported may be as much as several terabytes. A memory footprint of 128GB is more than enough storage to get a project started, through the proof of concept phase, and into deployment and initial scaling.
One of the points that Jacky makes during the webinar is that there are many projects that can be handled within the 128GB RAM capacity in which SingleStore is free to use, even when the project goes into production. At the point where you need SingleStore’s legendary support, and/or more capacity, a simple license switch and a reasonable monthly payment get you both.
We published a somewhat detailed description of how SingleStore works just a few weeks ago. To sum it up in a list:
SingleStore fits in very well into existing, often complex data processing architectures. The database works with a variety of other tools for data ingest and analytics. SingleStore runs on premises or in a public cloud. In containers and on virtual machines – anywhere you can run Linux.
The webinar features a straightforward demo of implementing an analytics app with SingleStore.
There are just four steps:
It’s worth taking a quick, well, look at our use of Looker to create the demo dashboard. Due to its thoroughgoing ANSI SQL support, SingleStore works well with the wide range of business intelligence (BI) tools that use SQL. A SingleStore database is also easily queried by anyone who knows standard SQL – a number that is certainly in the hundreds of thousands, and has been estimated to be more than a million people.
We used Looker for the demo because it gives users straightforward and direct access to the underlying database(s) being queried. This is especially advantageous for us at SingleStore, as our architecture is actually rather elegant, garnering a lot of praise – especially from users who come to SingleStore with a lot of previous database experience and some feel for what an “ideal”, distributed SQL database might look like. (You don’t have to take our word for it – find a few such people and ask them directly.)
Looker is easiest to use with standard SQL databases like SingleStore. And like many BI tools, it is also highly optimized specifically for use with SingleStore, and vice versa.
To get the most out of SingleStore, it’s very helpful to understand a few things about our distributed architecture. The webinar concludes with a brief description of it.
A SingleStore database is implemented as a series of master nodes and leaf nodes. Each master node has a copy of the database schema and a list of the data elements it’s responsible for. Several leaf nodes are managed by each master node. Applications and other clients connect to one of the aggregators, the Master Aggregator, that fields queries.
This webinar concluded with a lively Q&A period. The questions and answers include:
There were also comparative questions about other database solutions:
If you watch the webinar video, and have questions or feedback, feel free to email the main presenter, Jacky Liang, directly. He would also like to hear how you’re using the free tier. You can reach him at email@example.com.