InfluxDB and Redis operate in the database category with a focus on specific functionalities; InfluxDB is more suited for time-series data management while Redis excels in fast in-memory operations. InfluxDB has a competitive advantage in time-series data handling, whereas Redis is preferred for high-speed data access.
Features: InfluxDB offers strong data aggregation capabilities, integration with Grafana, and supports high workloads efficiently. It features a SQL-like query language which is intuitive for SQL users and provides useful plugins to enhance functionality. Redis is recognized for its speed due to in-memory nature, excellent caching capabilities that boost application efficiency, and diverse data structures for flexible data handling.
Room for Improvement: InfluxDB could improve its integration options, user interface complexity, and make its configuration process simpler. It would also benefit from enhancements in error logging and backup capabilities. Redis needs better documentation on scalability, a more user-friendly interface, and improved cluster management along with advanced security feature support.
Ease of Deployment and Customer Service: InfluxDB provides versatile deployment options including on-premises, public, and hybrid clouds, but may suffer from slow support response times, although community forums are strong. Redis is often deployed in public clouds, is easy to set up, and users find forums helpful, making direct technical assistance less necessary.
Pricing and ROI: InfluxDB is open-source, but costs can grow with scale due to price changes, though users see ROI in operational efficiency. Redis is also open-source and generally cost-effective; memory usage may incur costs, but it offers value for money in terms of speed and performance.
InfluxDB reduced my time to show data without any interruption, also reducing the number of people needed to manage the project; it is very good to have InfluxDB in my project.
The main challenge with InfluxDB, which is common with all databases, was handling very high throughput systems and high throughput message flow.
We’ve scaled on volume with seven years of continuous data without performance degradation.
InfluxDB's scalability is fine for me; I gather a lot of metrics and have not had any issues.
Data migration and changes to application-side configurations are challenging due to the lack of automatic migration tools in a non-clustered legacy system.
It serves as the backbone of our application, and its stability is crucial.
It is very stable, with no reliability or downtime in InfluxDB.
After integrating Kafka, it never broke again, as Kafka handled messages and metrics appropriately, decreasing the message throughput.
Redis is fairly stable.
InfluxDB deprecated FluxQL, which was intuitive since developers are already familiar with standard querying.
There is room for improvement, such as regarding backups and enhanced security through other types of authentication or encrypted data in TLS.
If better documentation were available, allowing me to find everything, including specific port numbers and procedures, it would have been much easier, and I wouldn't have had to spend time researching how to integrate InfluxDB with my Kafka producers and consumers.
Data persistence and recovery face issues with compatibility across major versions, making upgrades possible but downgrades not active.
We use the open-source version of InfluxDB, so it is free.
My experience with pricing, setup cost, and licensing for InfluxDB was great, as I did not use any license.
Since we use an open-source version of Redis, we do not experience any setup costs or licensing expenses.
The most important feature for us is low latency, which is crucial in building a high-performance engine for day trading.
InfluxDB has positively impacted my organization by solving a monitoring problem that we had, coming up with a solution since we did not have any monitoring system, allowing us to build one from scratch.
It helps me maintain my solution easily because it is very reliable, so we didn't face any performance issues or crashes regarding our queries; we can get the results very fast.
It functions similarly to a foundational building block in a larger system, enabling native integration and high functionality in core data processes.
| Product | Market Share (%) |
|---|---|
| Redis | 8.7% |
| InfluxDB | 5.9% |
| Other | 85.4% |
| Company Size | Count |
|---|---|
| Small Business | 5 |
| Midsize Enterprise | 3 |
| Large Enterprise | 8 |
| Company Size | Count |
|---|---|
| Small Business | 11 |
| Midsize Enterprise | 3 |
| Large Enterprise | 8 |
InfluxDB is open-source software that helps developers and enterprises alike to collect, store, process, and visualize time series data and to build next-generation applications. InfluxDB provides monitoring and insight on IoT, application, system, container, and infrastructure quickly and easily without complexities or compromises in scale, speed, or productivity.
InfluxDB has become a popular insight system for unified metrics and events enabling the most demanding SLAs. InfluxDB is used in just about every type of industry across a wide range of use cases, including network monitoring, IoT monitoring, industrial IoT, and infrastructure and application monitoring.
InfluxDB offers its users:
InfluxDB Benefits
There are several benefits to using InfluxDB . Some of the biggest advantages the solution offers include:
Reviews from Real Users
InfluxDB stands out among its competitors for a number of reasons. Two major ones are its flexible integration options and its data aggregation feature.
Shalauddin Ahamad S., a software engineer at a tech services company, notes, “The most valuable features are aggregating the data and the integration with Grafana for monitoring.”
Redis offers high-speed, in-memory storage, renowned for real-time performance. It supports quick data retrieval and is used commonly in applications like analytics and gaming.
Renowned for real-time performance, Redis delivers high-speed in-memory storage, making it a favorite for applications needing quick data retrieval. Its diverse data structures and caching capabilities support a broad array of use cases, including analytics and gaming. Redis ensures robust scalability with master-slave replication and clustering, while its publish/subscribe pattern renders it reliable for event-driven applications. The solution integrates smoothly with existing systems, minimizing performance tuning needs. Although documentation on scalability and security could be improved, Redis remains cost-effective and stable, commonly utilized in cloud environments. Enhancing integration with cloud services like AWS and Google Cloud and refining GUI may improve usability.
What are the key features of Redis?Redis finds application across industries for tasks like caching to improve application performance and speed, minimizing database load. It enables real-time processing for session storage, push notifications, and analytics. As a messaging platform, Redis handles high traffic and supports replication and clustering for cross-platform scalability.
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