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.
BUSINESS NEWS & EVENTS
Gartner Honorable Mention | 2021 Cloud Database Management Systems Magic Quadrant
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.
Study | How to shape the culture of a data-driven organization
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.
PRODUCT BLOGS & TUTORIALS
Release | CrateDB v4.7 is now stable and ready to use
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.
Blog | Indexing and Storage in CrateDB
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.
Tutorial | How to store files in 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.
Blog | Use CrateDB and Apache Superset for Open Source Data Warehousing and Visualization
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.
Tutorial | How to automate financial data collection and storage in CrateDB with Python and pandas
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.
Tutorials | CrateDB and Apache Airflow
In a series of tutorials on CrateDB and Apache Airflow we are showing you how to:
- Automate Data Export to S3
- Implement a Data Retention Policy
- Build a data ingestion pipeline
- Build a hot/cold storage data retention policy
- Build a data retention policy using external snapshot repositories