A Smooth Sea Never Made a Skillful Sailor

Today, I will demonstrate how ipython-sql can be leveraged in querying CockroachDB. This will require a secure instance of CockroachDB for the reasons I will explain below. Running a secure docker-compose instance of CRDB is beyond the scope of this tutorial. Instead, I will publish everything you need to get through the tutorial in my repo , including the Jupyter Notebook. You may also use CRDB docs to stand up a secure instance and change the url in the notebook to follow along.

Today, we're going to explore CockroachDB from the Data Science perspective again. We will continue to use Jupyter notebook but instead of Python, we're going to use the R language. I was inspired to write this post based on an article written by my colleague. I will build on that article by introducing Jupyter Notebook to the mix.

Today, we're going to explore CockroachDB from the Data Science perspective, using a popular exploratory web tool called Jupyter Notebook. I was inspired to write this post based on this article . The article goes over using Jupyter with Oracle, MySql and Postgresql, we're going to do the same with Cockroach! One caveat here is the heavy reliance on ipython-sql library. We're going to use Pandas library as the ipython-sql magic functions are not compatible with Cockroach today. Hopefully you will find it useful.

Today, we're going to evaluate Hadoop Ozone object store for CockroachDB object store sink viability. A bit of caution, this article only explores the art of possible, please use the ideas in this article at your own risk! Firstly, Hadoop Ozone is a new object store Hadoop Community is working on. It exposes an S3 API backed by HDFS and can scale to billions of files on prem! This article only scratches the surface, for everything there is to learn about Hadoop and Ozone , navigate to their respective websites.

Today, we’re going to explore CDC capability in CockroachDB Enterprise Edition using Minio object store as sink. To achieve this, we’re going to reuse the compose file from the first two tutorials and finally bring this to a close. Without further ado

This is my second post on creating a multi-service architecture with docker-compose. This is meant to be a learning exercise and typically docker-compose is used to set up a local development environment rather than a production-ready set up. I regularly, find myself building these environments to reproduce customer bugs. For a production-specific application, refer to your platform vendor documentation. At some later time, I will cover Kubernetes deployments that can be used as a stepping stone for a real-world application. Until then, let's focus on the task at hand. We're building a microservice architecture with CockroachDB writing changes in real-time to an S3 bucket in JSON format. S3 bucket is served by a service called Minio. It can act like an S3 appliance on premise or serve as a local gateway to your cloud storage. Let's dig in:

Over the next few weeks, I will be publishing a series of tutorials on CockroachDB and various third-party tools to demonstrate how easy it is to integrate CockroachDB into your daily work. Today, we're covering docker-compose and single-node Cockroach cluster as that will be a foundation for the next blog post.

This is a quick tutorial on exporting data out of SQL Server into CockroachDB. This is meant to be a learning exercise only and not meant for production deployment. I welcome any feedback to improve the process further. The fastest way to get started with SQL Server is via available Docker containers. I’m using the following tutorial to deploy SQL Server on Ubuntu from my Mac.  My SQL Server-Fu is a bit rusty and I opted for following this tutorial to restore WideWordImporters sample database into my Docker container. You may also need SQL Server tools installed on your host and you may find direction for Mac OS and Linux at the following site , users of Windows are quite familiar with download location for their OS. I also used the following directions to install SQL Server tools on my Mac but ran into compatibility issues with the drivers in my Docker container. This will be a debug session for another day. I will be working further on getting closer to a 1:1 ...