

PostgreSQL and InfluxDB are competitors in the database field, with PostgreSQL taking the upper hand due to its open-source flexibility and expansive feature set, which is appealing to a wide range of applications.
Features: PostgreSQL is known for its ACID compliance, extensive support for JSON and XML, and robust community backing. Its GIS functionalities and mature extension capabilities make it highly versatile. InfluxDB specializes in time-series data processing, offering rapid data ingestion, efficient storage, and real-time alerting features, making it ideal for environments requiring low latency.
Room for Improvement: PostgreSQL could improve usability for non-experts and refine its replication features. It also needs enhanced high availability support. InfluxDB could benefit from better documentation, simpler integration of tools like Chronograf, and more intuitive querying for SQL users. Improvements in scalability and backup features are also desirable.
Ease of Deployment and Customer Service: PostgreSQL's open-source nature allows for flexible deployment across various platforms, supported by a strong community, though professional support may require third-party services. InfluxDB is user-friendly in cloud environments but could enhance its user interface and support services, relying more on commercial support options.
Pricing and ROI: PostgreSQL is favored for its open-source model with no licensing costs, providing quick ROI and making it ideal for cost-conscious enterprises. InfluxDB, while also open-source, may have additional costs for scaling and enterprise features, with its ROI tied to strategic use of data volume.
These improvements translated into both cost savings and better service reliability, directly impacting business outcomes.
It simplifies processes and reduces the need for additional employees.
It has reduced a lot of time in terms of troubleshooting because the way it produces the data on a time-series basis allows me to collect and store the data for future reference.
They get on a call, resolve issues, and handle everything efficiently.
The InfluxDB support team was knowledgeable and helped us troubleshoot complex problems efficiently.
Obtaining that quantity of data directly from InfluxDB is quite challenging, and that is why we ask for help from the InfluxDB team to retrieve the data to avoid timeouts and those kinds of issues.
If PostgreSQL is hosted on cloud services such as Amazon RDS or Google Cloud SQL, the support is handled by the cloud provider, who provides automated backups, monitoring, infrastructure management, and technical support tickets.
Overall, we have a very small customer service team and a good engineering team with no overburden or bandwidth issues.
The main challenge with InfluxDB, which is common with all databases, was handling very high throughput systems and high throughput message flow.
It can handle large volumes of time-series data and with high ingestion rates, making it suitable for enterprise-scale deployments.
We’ve scaled on volume with seven years of continuous data without performance degradation.
Now, we are doing the same level of transactions in PostgreSQL, around 100,000 transactions, and we are getting good throughput with no latency.
It serves as the backbone of our application, and its stability is crucial.
We have used it to support mission-critical systems with continuous data ingestion and real-time analytics.
It is very stable, with no reliability or downtime in InfluxDB.
I have never seen any performance issue in PostgreSQL.
InfluxDB deprecated FluxQL, which was intuitive since developers are already familiar with standard querying.
Having a SQL abstraction in InfluxDB could be beneficial, making it more accessible for teams that prefer querying with SQL-style syntax.
It could include automated backup and a monitoring solution for InfluxDB or a script developed by a REST API.
Query optimization improves slow queries by using proper indexes, avoiding unnecessary joins, and using EXPLAIN ANALYZE to inspect query plans.
If I need to increase the dimension to 3,000 or 5,000, that option should be available.
We use the open-source version of InfluxDB, so it is free.
I find the cloud version pricing of InfluxDB reasonable, and for the on-premises solution we use in our service, we need to purchase licenses.
Pricing is based on data volume, retention, and features, which really makes it scalable but requires careful planning to avoid unexpected costs.
Even with doing 100,000 transactions right now within PostgreSQL, we are happy with PostgreSQL and not seeing that it is expensive or going out of budget.
The most important feature for us is low latency, which is crucial in building a high-performance engine for day trading.
InfluxDB’s core functionality is crucial as it allows us to store our data and execute queries with excellent response times.
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.
PostgreSQL improves reliability, performance, and scalability in production. Since it is ACID compliant, it ensures that database transactions are safe and consistent, preventing partial data updates, maintaining data integrity, and allowing multiple users to read or write data simultaneously using MVCC.
The best feature is performance, because of which I decided on PostgreSQL.
| Product | Mindshare (%) |
|---|---|
| PostgreSQL | 13.1% |
| InfluxDB | 4.9% |
| Other | 82.0% |


| Company Size | Count |
|---|---|
| Small Business | 9 |
| Midsize Enterprise | 5 |
| Large Enterprise | 9 |
| Company Size | Count |
|---|---|
| Small Business | 57 |
| Midsize Enterprise | 27 |
| Large Enterprise | 48 |
InfluxDB offers efficient time series data handling with fast writes, optimized storage, and seamless Grafana integration, making it ideal for high-volume applications like crypto trading and real-time monitoring. Its SQL-like query language and cloud-based options enhance user experience and system scalability.
InfluxDB stands out with its ability to handle high-volume time series data efficiently, thanks to fast data writes and efficient compression. It is highly scalable, providing clustering features for improved performance management. Integration with Grafana enhances visualization, making it easier to analyze complex data through a user-friendly SQL-like query language. Real-time monitoring, historical data access, and proactive alerts enhance system reliability. Its cloud offering simplifies maintenance and operations, making it attractive for users seeking an efficient time series database.
What are the key features of InfluxDB?InfluxDB is applied extensively in industries handling high-volume data needs. For sensor data storage in production environments, it offers reliable performance. Its role in server management metrics and performance monitoring is crucial for maintaining optimal operations. In crypto market data collection, it supports fast-paced trading environments. Industries use it for real-time tracking, like maritime vessel monitoring, leveraging its rapid data handling and visualization capabilities. Its applications also extend to IoT environments, API performance tracking, HVAC systems, and log aggregation, often integrating with Prometheus, Docker, and AWS to enhance system capabilities.
PostgreSQL is a versatile and reliable database management system commonly used for web development, data analysis, and building scalable databases.
It offers advanced features like indexing, replication, and transaction management. Users appreciate its flexibility, performance, and ability to handle large amounts of data efficiently. Its robustness, scalability, and support for complex queries make it highly valuable.
Additionally, PostgreSQL's extensibility, flexibility, community support, and frequent updates contribute to its ongoing improvement and stability.
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