Hi there,
In this newsletter, we share several tutorials and blog posts to help you get the most out of CrateDB. Plus, some news about our new solution CrateOM, events, and an honorable mention.
Gartner's Magic Quadrant for Cloud Database Management Systems shows that the cloud DBMS space is experiencing massive growth for cloud based databases. We are very proud that CrateDB's cloud capabilities garnered an Honorable Mention among leading database technologies.
Ride the new wave of the data-driven organization and learn best practices from a global survey of 434 participants in this study by independent analyst firm BARC.
With the release of CrateDB v4.7 we are adding improvements based on our customer and user feedback in SQL compatibility, scalar and aggregate functions, and PostgreSQL compatibility.
In this blog article, we start from the bottom of the CrateDB architecture and gradually move up to higher layers, presenting the most critical aspects of CrateDB.
CrateDB can be used to store binary large objects (Blobs). This allows you to store binary data (e.g. product photos, PDFs, etc) in a table which will be automatically sharded and replicated across your cluster.
In this post, we will show you how to get started with CrateDB and Apache Superset, an easy-to-use open-source business intelligence (BI) application that offers a rich set of customizable data visualizations. Create your first Superset visualizations running on top of CrateDB data in no time.
This tutorial will teach you how to automatically collect historical data from S&P-500 companies and store it all in CrateDB using Python. In a follow-up tutorial, you will learn how to adapt the Python code to run as an Apache Airflow DAG.
In a series of tutorials on CrateDB and Apache Airflow we are showing you how to: