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Aside from ensuring each service is working properly, one of the most challenging parts of managing a cloud-based infrastructure is cost monitoring. There are countless services to keep track of—including storage, databases, and computation—each with their own complex pricing structure. Monitoring cloud costs is quite different from other organizational costs in that it can be difficult to detect anomalies in real-time and accurately forecast monthly costs.

Although the differences between PostgreSQL vs. MySQL lessen with each passing year, both database systems continue to offer distinct advantages for different use cases. In this guide, we’ll take a detailed look at the characteristics of PostgreSQL vs. MySQL – and why you might choose one DBMS over the other.

Oracle Database is one of the world’s leading relational database management systems (RDBMS) offering high performance, robust security, and a wide range of capabilities for businesses who want to build and deploy applications in the cloud. Here’s how DreamFactory works best with Oracle.

The Cloudera Operational Database (COD) experience is a managed dbPaaS solution which abstracts the underlying cluster instance as a Database. It can auto-scale based on the workload utilization of the cluster and will be adding the ability to auto-tune (better performance within the existing infrastructure footprint) and auto-heal (resolve operational problems automatically) later this year.

A Shift Towards Industry 4.0 Is Improving Manufacturing Efficiency And Increasing Innovation In Part II of our series with Michael Ger, Managing Director of Manufacturing and Automotive at Cloudera, he looks in greater detail at how AI, big data, and machine learning are impacting connected living and the evolution of autonomous driving.

Here's why you need to double down on your DataOps before your vacation. In the past few months, everything has changed at work (or at home). Q1 plans were scrapped. Reset buttons were smashed. It was all about cost-cutting and keeping lights on. Many app and data teams sought quick solutions and developed workarounds to data challenges and operational problems as people prepared to work from home for the foreseeable future. And now, it’s time for a holiday.

How can you avoid wasting engineering cycles around data pipeline creation and maintenance? Answer: Powered By Fivetran

Welcome back to another one of our Community Roundups, folks! Summer is halfway gone, but we hope you’re having a great time nonetheless. Let’s take a look at what’s been going on in the community!

When migrating a data warehouse to BigQuery, one of the most critical tasks is mapping existing user permissions to equivalent Google Cloud Identity and Access Management (Cloud IAM) permissions and roles. This is especially true for migrating from large enterprise data warehouses like Teradata to BigQuery. The existing Teradata databases commonly contain multiple user-defined roles that combine access permissions and capture common data access patterns.