NoSQL Database Monitoring

Compared to SQL database that handle structure data about the relationships between clients, tables, variables, and other entities, NoSQL databases introduce greater flexibility and scalability into database storage with their non-tabular and non-relational model, which allows different database types to be used to effectively support different kinds of data storage.

NoSQL databases and other non-relational databases can still store relational data, and in some cases, relationship data can be modelled more efficiently in NoSQL databases, since the relational data doesn’t need to be distributed across multiple tables. This is because they allow for related data to be consolidated into one data structure.

There are four primary kinds of NoSQL databases:

• Document: These databases allow documents to be efficiently stored, nested, and accessed similar to how applications use data objects. They also allow for indexing to reduce query response times.
• Key value: Somewhat akin to a two-column relational table, these NoSQL databases store data elements with a key (or attribute name) and a corresponding value. These streamlined NoSQL databases are useful for managing online shopping carts and end user profiles or preferences.
• Column: These NoSQL databases organize data into smaller sets of columns, which provides efficient data compression and enables faster database reads. These databases are particularly useful for running analytics.
• Graph: This database structure directly stores relational information and connections between distinct data elements, which can be helpful for fraud detection.

The flexibility of NoSQL data structures and their applications is one of the primary benefits of NoSQL databases. NoSQL databases help address some of the limitations of traditional relational database management systems (DBMSs). For instance, traditional database structures rely on tables to store data—which can prevent some information structures from being represented within the database without first altering the data or applications involved. NoSQL structures also allow versioning, which helps ensure historical data is logged and not written over when data changes.

NoSQL databases can also provide superior performance over traditional RDBMSs when it comes to normalizing data. Normalization increases the number of internal database operations, which can quickly cause a traditional relational RDBMS to expand to terabytes in size, whereas NoSQL databases are designed to remain lightweight and efficient at scale. NoSQL databases are also optimized for developer productivity.

Since NoSQL database structures are relatively lightweight, this enables them to be used for extremely sophisticated applications, such as fraud detection. By pairing the speed of NoSQL database structures with that of automated and machine learning tasks, thousands of transactions can be audited per second, which allows for far faster detection of potentially fraudulent activity.

As the NoSQL data model scales efficiently, this can also allow for greater data storage while also increasing query speed. However, as data volumes increase in size, the complexity of a company’s NoSQL database performance monitoring requirements also increase.

Modern NoSQL DB real-time monitoring uses the speed and power of modern analytics to track database performance and resource usage in granular detail. NoSQL database performance monitoring helps give you visibility into current health metrics, so you have the information you need to make decisions that can help maximize uptime to better support business critical processes and operations.

Some key performance metrics include connections, key read/write requests, memory utilization, table locks, threads data, and transaction rates.

However, while NoSQL databases are built to efficiently store vast amounts of data, it’s vital to adopt a NoSQL DB real-time monitoring solution with actionable insights and powerful analytics as company size and number of database queries increase. Comprehensive NoSQL database performance monitoring tools can provide real-time and historical database insights—because when you have a clear picture of your database performance, you can have a better idea how to best resolve issues as they arise.

Databases are the backbone of the web applications businesses rely on to carry out everyday operations. As companies grow larger and need to support more rapid app development, scalability and speed are more critical now more than ever, which is why database structures have shifted to support these resource needs.

However, to ensure optimal performance, databases require maintenance and tuning. NoSQL database monitoring tools can collect, organize, and analyze performance metrics with speed and accuracy that can be difficult to accomplish manually—making these monitoring solutions an essential part of proactive management of NoSQL databases.

Database server monitoring tools can track system resources and notify you when utilization nears or reaches critical thresholds. Proactive NoSQL database monitoring tools can also help you more easily maintain optimum performance by connecting to the database source for granular analysis of collected queries, which can reveal valuable insights to help speed up the troubleshooting process.