Operations | Monitoring | ITSM | DevOps | Cloud

SQL and NoSQL are two database technologies widely adopted by many organizations for different use cases. Both technologies share the common goal of efficiently processing and managing data. Still, there are some significant differences. This article compares SQL and NoSQL, exploring their key differences in terms of language, structure, scalability, properties and support. We’ll also discuss examples, pros and cons and the most suitable application areas for each database type.

Alerting is one of the main reasons for having a monitoring system. It is always better to be notified about an issue before an unhappy user or customer gets to you. For this, engineers build systems that would check for certain conditions all the time, day and night. And when the system detects an anomaly - it raises an alert. Monitoring could break, so engineers make it reliable. Monitoring could get overwhelmed, so engineers make it scalable. But what if monitoring was just poorly instructed?

In this series of blog posts, we speak with database professionals from financial services organizations around the world to better understand how DevOps is shaping the sector. On the way, we dig into key current factors including the rise of technology upstarts in fintech and insurtech, the speed of digital transformation, and the ever-increasing threat of cyberattacks.

This article was originally published in The New Stack and is reposted here with permission. It’s tempting to stuff time series data into the familiar Postgres or MySQL database, but that’s a bad idea for many reasons. To the uninitiated or unfamiliar, time series data exhibits similar characteristics to relational data, but the two data types have some critical differences.

It’s a constant challenge for many businesses: where and how to focus investment in technology to remain competitive and stay current with the latest trends and development practices, while still meeting changing customer demands.

Oracle Database is an enterprise multi-model database system capable of handling large amounts of data across multiple database servers with support for a wide variety of workloads. It’s a widely used and proven database software, so we are incredibly pleased to announce that it now has a dedicated cloud integration in Grafana Cloud. With the Oracle Database (OracleDB) integration, you can monitor your database’s performance with ease.

At Datadog, we’re constantly developing new integrations to give you complete, end-to-end visibility into your entire system. Here are just a few of our latest releases.

Netdata Agent is an open-source monitoring agent capable of collecting metrics from various sources and visualizing them in real-time. It is able to discover and collect metrics with zero configuration, providing a quick and easy way to monitor systems.

Managing an IT team is a tough job. While demands on services are increasing, both internally and externally, the need to be aware of and in control of application and server performance is a constant pressure. Right now, there are four key areas that are of particular concern for those responsible for IT departments and teams.

Memory databases are known for their ability to store and manage large volumes of data in memory. Their memory-based architecture allows users to quickly retrieve critical information and benefit from performant data reading. Thanks to these characteristics, businesses use memory databases for various applications that require prompt data access playing a vital role within their digital resources.