FastoRedis (fork of FastoNoSQL) - is a cross-platform open source Redis management tool (i.e. It put the same engine that powers Redis's redis-cli shell. Everything you can write in redis-cli shell — you can write in Fastoredis! Redis Management Tool. Scale up, scale down, inspect and monitor. Redis Cluster with ease. RedisInsight provides an intuitive and efficient GUI for Redis, allowing you to interact with your databases and manage your data—with built-in support for most popular Redis modules. It provides tools to analyze the memory, profile the performance of your database usage, and guide you toward better Redis usage.
Remote Dictionary Server (Redis) is a widely used NoSQL database systems. It’s an open-source in-memory data store known for its high processing speed and performance. It allows quick information delivery and supports several data structures, including strings, lists, hashes, sets, sorted sets, bitmaps, streams, and more. Redis is multi-faceted and supports an array of use cases across industries, including real-time analytics, caching, session management, media streaming, and messaging, among others. In-memory data storage eliminates the need to access data from the disk and thereby eliminates seek-time delays.
Redis databases have an edge over other databases due to flexible data structures and data persistence. However, Redis performance monitoring remains critical, as the database directly impacts application performance. It’s imperative to assess whether the required processes are running as expected, queries are getting executed effectively, and bottlenecks are being identified proactively. To ensure a high level of performance, you should employ an efficient Redis monitoring tool that provides a holistic view of the Redis database and allows tracking Redis performance metrics.
Let’s look at key Redis monitoring tools to help streamline Redis database management and monitoring processes to improve performance and boost efficiency.
SolarWinds AppOptics
Integrating SolarWinds® AppOptics™ with Redis is an effective way to monitor the Redis database for identifying and troubleshooting the root of performance issues. The AppOptics integration with Redis allows monitoring key Redis performance metrics from a single place. The central AppOptics dashboard provides clear insights across relevant metrics, including uptime metrics, memory metrics, and other Redis internal metrics. Redis monitoring with AppOptics provides insight into the client metrics such as the number of clients connected to a Redis server, the number of attempted clients connections, and the number of clients rejected from the connection. AppOptics also allows users to create custom tags for different categories of Redis performance metrics for better management and quick monitoring.
OpsDash
OpsDash is quick to set up. Its pre-configured dashboards give a holistic view and an instant insight into key performance metrics to assess the health of Redis instances. A quick look at the dashboard provides a clear picture of memory usage, in-memory items, number of operations performed per second, cache hit rate, and other relevant performance areas. It also allows tracking custom metrics and lets the users set critical upper limits for metrics to proactively identify potential bottlenecks.
Dynatrace
Dynatrace provides visibility into individual database statements by allowing users to monitor and analyze Redis databases across all platforms. It lets users track critical Redis performance metrics. Dynatrace offers process-level visibility by tracking network metrics to help users keep track of sudden performance issues. Smart data visualization helps you understand how applications use database resources quickly. Furthermore, detailed metrics help ensure quick root cause analysis to find out which commands affect the database performance the most.
ManageEngine Applications Manager (Redis Monitor)
Applications Manager’s Redis monitor provides critical information about database memory, network traffic, and overall system infrastructure. It allows users to track memory specific metrics such as memory usage, memory fragmentation ratio, and cache hit ratio, among others. Network parameters, including the number of connected and blocked clients, number of concurrent connections, rejected connections, and other connection stats are also easily trackable. Applications Manager’s Redis performance monitoring tool also provides a fault management system to effectively identify the root cause of performance issues and detect anomalies for proactive troubleshooting. It also supports aggregation and visualization of key metrics with the help of extensive and in-depth reports for better performance monitoring and analysis.
SolarWinds Database Performance Monitor (DPM)
SolarWinds DPM is a cloud-based Redis database manager designed to monitor every query and metric on the Redis system. It offers both real-time and historical analysis to detect and resolve performance issues. DPM is designed to drill down from a global viewpoint to a single query on a single server promptly and allows cross-correlations among relevant metrics to get to the root cause of performance issues. Powered by sophisticated big data analytics techniques, such as regression analysis and queuing theory, SolarWinds DPM provides deep insight into Redis metrics and facilitates smart alerting to raise the alarm about potential performance issues before they become a substantial roadblock. SolarWinds DPM automatically discovers the corresponding system requirements to get started.
Conclusion
Redis is a powerful database system used by performance-intensive applications, since it supports sub-millisecond response times. Redis databases support mission-critical applications for many businesses across industries, so the need to proactively monitor and fine-tune the database performance is all the more important to take full advantage of its potential. Redis returns an array of metrics for each command, and tracking these metrics helps ensure the system’s health. We recommend integrating Redis metrics with a dynamic Redis monitoring tool such as SolarWinds AppOptics to get a complete view of your Redis database. AppOptics helps you monitor and analyze a comprehensive set of relevant metrics while quickly performing root cause analysis for performance-related issues to accelerate troubleshooting. Get hands-on experience with a full-featured 30-day free trial now and gain deeper visibility into the health and performance of your Redis database server.
What is Redis?
Redis (for REmote DIctionary Server) (link resides outside IBM) is an open source, in-memory, NoSQL key/value store that is used primarily as an application cache or quick-response database. Because it stores data in memory, rather than on a disk or solid-state drive (SSD), Redis delivers unparalleled speed, reliability, and performance.
When an application relies on external data sources, the latency and throughput of those sources can create a performance bottleneck, especially as traffic increases or the application scales. One way to improve performance in these cases is to store and manipulate data in-memory, physically closer to the application. Redis is built to this task: It stores all data in-memory—delivering the fastest possible performance when reading or writing data—and offers built-in replication capabilities that let you place data physically closer to the user for the lowest latency.
Other Redis characteristics worth noting include support for multiple data structures, built-in Lua scripting, multiple levels of on-disk persistence, and high availability.
Differentiating capabilities
Redis stands apart from ‘traditional’ NoSQL data stores as an auxiliary component designed specifically to improve application performance. Here are a few differentiating capabilities of Redis:
Redis cache sessions
Again, unlike NoSQL databases such as MongoDB and PostreSQL, Redis stores data in the server's main memory rather than on hard disks and solid-state drives. This leads to significantly faster response times when performing read and write operations. It also helps ensure high availability (together with Redis Sentinel—see below) and scalability of services and application workloads.
Redis queues
Redis can queue tasks that may take web clients longer to process than usual. Multiprocess task queuing is commonplace in many of today's web-based applications, and Redis makes it easy to implement automated Python-written processes that run in the background of request/response cycles.
Redis data types
While technically a key/value store, Redis is an actual data structure server that supports multiple data types and structures, including the following:
- Unique and unsorted string elements
- Binary-safe data
- HyperLogLogs
- Bit arrays
- Hashes
- Lists
Redis client handling
Redis features native client integration capabilities to help developers manipulate and interact with their data. There are currently well over 100 different open source clients available in the Redis client library, and developers can easily add new integrations to support additional features and programming languages.
Features
Redis Management Tool
Some of the most important or noteworthy features of Redis include the following:
Redis Sentinel
Redis Sentinel (link resides outside IBM) is a stand-alone distributed system that helps developers calibrate their instances to be highly available for clients. Sentinel uses a series of monitoring processes, notifications, and automatic failovers to inform users when there is something wrong with master and slave instances, while automatically reconfiguring new connections for applications when necessary.
Redis Cluster
Redis Cluster (link resides outside IBM) is a distributed implementation of Redis that automatically splits datasets among multiple nodes. This supports higher performance and scalability of database deployments, while ensuring continuous operations in the event that node subsets are unable to communicate with the rest of the cluster.
Redis Pub/Sub
Because Redis supports the use of publish and subscribe (Pub/Sub) commands (link resides outside IBM), users can design high-performance chat and messaging services across all their applications and services. This includes the ability to use list data structures to run atomic operations and blocking capabilities.
Redis persistence
Redis uses persistent disk storage (link resides outside IBM) designed to survive process outages and network bottlenecks. Redis can persist datasets by taking regular snapshots of data and appending them with changes as they become available. Redis can then be configured to generate these database backups on demand or at automatic intervals to ensure database durability and integrity.
Redis vs. Memcached
Both Redis and Memcached are open source, in-memory data stores, but they differ when it comes to their benefits and features. Memcached is often the preferred choice for simple applications requiring fewer memory resources, but it is limited when storing data in its serialized form. Redis' use of data structures provides much more power when working with large datasets and more ability to fine-tune cache contents and maintain greater efficiency in specific application scenarios.
Redis vs. MongoDB
While Redis is an in-memory database store, MongoDB is known as an on-disk document store. Although both solutions are built for different purposes, they are often used together to maximize the speed and efficiency of a NoSQL database. Because of its caching ability, Redis can locate required data extremely quickly, serving as an ingestion buffer that makes MongoDB more efficient and able to manage larger frequencies of document updates in near real-time. With MongoDB’s ability to store significant amounts of data and Redis’ ability to process it faster, the pairing offers a powerful database management solution for a variety of use cases.
Use cases
Here are some common use cases that enterprises benefit from when working with Redis:
- Real-time analytics: Because Redis can process data with sub-millisecond latency, it is ideal for real-time analytics, online advertising campaigns, and AI-driven machine learning processes.
- Location-based applications: Redis simplifies the development of location-based applications and services by providing geospatial indexing, sets, and operations. Using sorted sets, Redis is able to offload time-consuming searching and sorting of location data while also using an intelligent geo-hashing implementation.
- Caching for databases: Redis is able to handle large amounts of real-time data, making use of its in-memory data storage capabilities to help support highly responsive database constructs. Caching with Redis allows for fewer database accesses, which helps to reduce the amount of traffic and instances required. By using Redis for caching, development teams can dramatically improve their application throughputs by achieving sub-millisecond latency. And since Redis’ caching layer can scale quickly and economically, organizations are able to develop these highly responsive applications while reducing their overall expenditures.
Installing Redis
Getting started with Redis is a fairly seamless process, especially with the use of the Redis Desktop Manager (RDM) (link resides outside IBM). And since Redis and RDM are open source, active development communities are always working to improve their efficiency of operation and continuously evolve supported tools and integrations.
For more information on installing and setting up Redis, follow the setup instructions in the community (link resides outside IBM).
Redis Tool
Redis and IBM
When managing large enterprise databases, organizations often find it difficult to monitor their application performance while still having time to scale their infrastructure and develop new processes.
IBM Cloud Databases for Redis is a fully managed solution for implementing Redis' powerful in-memory caching capabilities into your modern application stack. Databases for Redis is an enterprise-ready solution that allows you to scale disk and RAM independently, giving you the flexibility you need to meet the growing resource demands of the most innovative application requirements. Databases for Redis also features a Cache-mode, allowing you to optimize you Redis usage to improve application and database performance.
Redis Tool Free
IBM's team of database experts focus on making sure the database is up and running so that you can focus on your applications. IBM provides high availability, flexible scaling options, and consumption-based pricing. To learn more about finding the right tool for the job, see 'How to Choose a Database on IBM Cloud.'
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