Elasticsearch is primarily a search engine optimized for fast, complex search queries, especially text searches, and is often used for log and event data analysis. MongoDB, on the other hand, is a general-purpose, document-oriented database that excels in storing and retrieving structured and semi-structured data. It is commonly used for mobile, social, and IoT applications. While Elasticsearch provides superior search capabilities, MongoDB offers more robust data processing and storage features.

A large proportion of our customers rely on eG Enterprise to monitor and troubleshoot application and end-user experience problems caused by problems in underlying database dependencies. Our end-to-end unified monitoring and root-cause analysis platform supports all major database technologies. Over recent years, we have witnessed a significant shift from traditional on-premises databases to more dynamic, scalable solutions.

Monitoring Redis instances is essential for maintaining performance, reliability, and security. It allows you to detect issues early, optimize resources, and provide a seamless experience for both developers and end-users. Monitoring your database allows you to track key performance metrics such as memory usage, CPU usage, and query response times. By analyzing these metrics, you can identify performance bottlenecks, optimize queries, and ensure that Redis is operating efficiently.

Datadog Database Monitoring (DBM), which provides host-level and query performance metrics and insights for PostgreSQL, MySQL, and SQL Server, is now available for Oracle. Oracle is one of the most common database types, and now teams that operate Oracle databases can use Datadog to monitor these resources alongside telemetry from across their environments.

In the ever-evolving landscape of data management, Oracle databases stand as stalwarts, driving critical operations for countless organizations worldwide. Yet, the complexity of these environments presents a formidable challenge in monitoring them effectively. Efficient monitoring is the cornerstone of ensuring optimal performance, security, and compliance within Oracle ecosystems. However, the multifaceted nature of Oracle databases poses several challenges that demand nuanced solutions.

Monitoring PostgreSQL for performance issues is critical. PostgreSQL is a powerful open-source relational database system that stands out for its robustness, scalability, and strong emphasis on extensibility and standards compliance. In this guide on PostgreSQL monitoring, we will cover key PostgreSQL metrics that should be monitored, best practices for monitoring PostgreSQL and some tools with which you can set up PostgreSQL monitoring.

Aiven for PostgreSQL® adds support for major version 16. Find out what the key improvements are and how you can get the new version.

PostgreSQL metrics monitoring is important to ensure that PostgreSQL is performing as expected and to identify and resolve problems quickly. In this tutorial, you will install OpenTelemetry Collector to collect PostgreSQL metrics and then send the collected data to SigNoz for monitoring and visualization. In this tutorial, we cover: If you want to jump straight into implementation, start with this prerequisites section.

For users using monitoring module, migrating their custom dashboards, navigation items and permissions and restrictions to Icinga DB Web has been made easier with the recent Icinga DB Web release (v1.1.1) through its migrate command. Once Icinga DB Web has been upgraded to v1.1.1, run the command icingacli icingadb migrate --help to see the avaliable actions under migrate command and what each action does.

Jason Mallory is a senior MySQL/SQL server database administrator who develops monitoring and alerting solutions for operations departments in the aerospace industry. Jason is also a Grafana Champion. MySQL Network Database — or NDB, for short — is an in-memory, sharded database platform. Consisting of several moving parts, NDB can be one of the most challenging database platforms to monitor. However, monitoring NDB cluster health is crucial to ensure reliability and performance.

Monitoring your PostgreSQL instance is essential for maintaining performance, reliability, security, and compliance. It allows you to stay ahead of potential issues, optimize resource utilization, and ensure a smooth and efficient operation of your database system. Database monitoring helps you can pinpoint problematic queries, analyze execution plans, and make necessary adjustments to improve overall application responsiveness.

SQL Monitor is an essential tool for DBA teams worldwide, providing real-time monitoring of SQL Server and PostgreSQL performance. With SQL Monitor, you can easily track deployments, errors, and other events on the timeline. This feature, called annotations, allows you to quickly identify the root cause of performance issues and take corrective action. SQL Monitor’s timeline is a powerful tool that helps you stay on top of your database performance and keep your systems running smoothly.

Are you looking for MongoDB monitoring tools? Then you’re at the right place. MongoDB is one of the most popular and powerful NoSQL databases out there. The fact that it’s a document-based database makes it blazing fast. With all the features that MongoDB comes with, you need to keep an eye on your MongoDB's health and performance - especially as it directly deals with your data. There are many monitoring tools out there, and choosing the right one can be confusing.

The net result of an AI-powered optimization process is not only a better data experience, but also increased developer productivity. Once the teams are aware of what can be automated, the improvements can not only speed things up but reduce costs.

OpenTelemetry can help you monitor CouchDB performance metrics with the help of OpenTelemetry Collector. In this tutorial, you will install OpenTelemetry Collector to collect CouchDB metrics and then send the collected data to SigNoz for monitoring and visualization. Before that, let’s have a brief overview of CouchDB. If you want to jump straight into implementation, start with this Prerequisites section.

Database monitoring refers to the continuous process of tracking and analyzing the health and performance of a database. It’s essentially a regularized health check-up for your data management system that diagnoses anomalies and helps identify potential issues before they escalate. By persistently monitoring databases, you can ensure that they’re functioning optimally and there is no obstruction of data flows to dependent resources.

MongoDB is renowned for its ability to scale horizontally, accommodate dynamic schemas, and deliver high-performance results. However, the seamless operation of any database, including MongoDB, relies heavily on efficient monitoring to uncover insights, identify potential bottlenecks, and proactively address issues that may compromise performance and reliability.