A NoSQL database provides a mechanism for data storage and retrieval, without using the tabular relations associated with relational databases. Originally referred to as "non-SQL" or "non-relational" databases, NoSQL databases are increasingly used in big data and real-time web application environments. NoSQL systems are also sometimes called “Not only SQL” to emphasize that they may support SQL-like query languages or sit alongside SQL databases in polyglot-persistent architectures.
Well-suited for enterprise grade adoption, NoSQL databases are built to be flexible, scalable, and capable of rapidly responding to the data management demands of modern businesses.
Following are four of the most popular types of NoSQL databases:
- Document databases. These databases are primarily built for storing documents, including JSON and XML documents.
- Wide-column databases. These databases use the tabular format of relational databases yet allow a wide variance in how data is named and formatted in each row, even in the same table. Like key-value stores, wide-column databases have some basic structure while also preserving a lot of flexibility.
- Graph databases. Graph databases use graph structures to define the relationships between stored data points. These databases are useful for identifying patterns in unstructured and semi-structured information.
- Key-value stores. Key-value stores group associated data in collections and identify records with unique keys to enable easy retrieval. Key-value stores have just enough structure to mirror the value of relational databases, while still preserving the benefits of NoSQL.
Figure 1: SQL vs NoSQL databases.
To support IT services effectively, NoSQL databases need to deliver the following key capabilities:
- Support large numbers of concurrent users, potentially ranging from tens of thousands to millions.
- Deliver highly responsive experiences to a globally distributed base of users.
- Provide continuous availability, with no downtime.
- Handle semi-structured and unstructured data.
- Offer rapid adaptability in order to accommodate changing requirements, frequent updates, and new features.
Key challenges in adopting any big data technology are usually human rather than technical. Multi-tier architectures with multiple components introduce multiple failure points. Administrators need a comprehensive view of relevant performance metrics from across all the tiers within NoSQL database implementations.
Based on use case, a typical modern data centre will have one or more of the following NoSQL technologies working simultaneously to support a service line:
Figure 2: Popular NoSQL databases in use across industries. (Picture credit: https://www.complexsql.com/difference-between-sql-and-nosql/ )
DX Unified Infrastructure Management (DX UIM) offers the widest range of probes. With the solution, IT operations teams across industries can reduce tool sprawl and get consistent, single-pane-of-glass visibility across the technology stack.
Following are a few of the popular out-of-the-box monitoring probes DX UIM offers for NoSQL databases today:
MongoDB Monitoring
The MongoDB monitoring probe uses OS commands and MongoDB API calls to monitor MongoDB. The probe monitors the performance and resource use of a single node in the MongoDB cluster. It collects these key metrics across the following key components:
System components monitored:
- CPU
- Memory
- Network
- Storage Volumes
Cluster components monitored:
- Cluster Router
- Cluster Configurations
- Replication Servers (Primary and Secondary)
- Replication Arbiter
- Standalone
Redis Monitoring
With DX UIM’s Redis monitoring probe, teams can track both standalone and clustered Redis environments. The probe monitors application resource usage, health metrics, and application processes. It also tracks services status, usage, and throughput metrics, including number of queries processed, response times, queue size, and more.
The probe collects key metrics across the components that are part of a Redis deployment:
- Cluster
- Client
- Keyspace
- Memory Monitors
- Performance
- Persistence
- Replication
Amazon DynamoDB Monitoring
DX UIM offers AWS web services monitoring, a single probe that can monitor all AWS services. For AWS DynamoDB monitoring, the probe generates QoS and alarm messages that are based on the performance and operations of the database.
The probe uses the sum statistics on the collected values for the following DynamoDB metrics:
- Read Throttle Events
- Write Throttle Events
- System Errors
- Put Item Throttled Requests
- Delete Item Throttled Requests
- Update Item Throttled Requests
- Get Item Throttled Requests
- Batch Get Item Throttled Requests
- Batch Write Item Throttled Requests
- Scan Throttled Requests
- Query Throttled Requests
- Get Records Throttled Request
Cassandra Monitoring
The Cassandra monitoring probe is part of Hadoop 2.0 ecosystem probes portfolio offered in DX UIM. This probe monitors internal performance and resource usage throughout a node in a Cassandra cluster. To realize a comprehensive monitoring experience, the Cassandra monitoring probe should be installed on each node in the Cassandra cluster.
The probe uses operating system commands, Cassandra API calls, and the Cassandra-supported JMX layer. DX UIM presents the information to the cluster administrator as metrics, alarms, and reports. Users can select and schedule an extensive range of checkpoints, depending on their specific monitoring requirements. The probe collects key metrics across clusters and nodes in the deployment.
Figure 3: Metric viewer across technologies.
One of the key benefits of using DX UIM for NoSQL monitoring is that it offers a non-invasive approach that keeps NoSQL systems secure. The solution’s remote, agentless monitoring supports baselining and trend analysis over time. As with other technology environments, DX UIM offers multi-tenancy support and sophisticated service level management in NoSQL environments.
DX UIM helps track all the critical elements that can affect the end user experience, providing holistic monitoring of the most adopted NoSQL technologies, such as MongoDB, Cassandra, Redis, and DynamoDB. The solution offers a single unified management platform that enables teams to deliver better end user experiences.