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Grafana vs Papertrail: What are the differences?
Introduction
Grafana and Papertrail are two popular tools used for monitoring and visualizing logs in a website. While they both offer similar functionalities, there are key differences between the two. This article will highlight and explain six specific differences between Grafana and Papertrail.
Architecture: Grafana is a time-series analytics platform that provides a web-based interface for creating and sharing dashboards. It can be used with various data sources and supports multiple databases, including Graphite, InfluxDB, and Prometheus. On the other hand, Papertrail is a cloud-hosted log management service that centralizes logs in real-time and allows users to search and analyze them using a web-based interface. Unlike Grafana, Papertrail is specifically designed for log management.
Visualization: Grafana excels at data visualization and provides a wide range of visualizations, including graphs, charts, and tables. It allows users to create interactive dashboards with customizable panels and supports advanced features like annotations, templating, and alerting. In contrast, Papertrail focuses more on search and filtering capabilities rather than visualization. While it provides basic visualization options like line graphs, it lacks the extensive visualization features offered by Grafana.
Alerting: Grafana offers robust alerting capabilities that allow users to set up rules and notifications based on metrics and thresholds. It supports various notification channels like email, Slack, and PagerDuty. Users can configure alerts based on specific conditions and receive real-time alerts when those conditions are met or breached. On the other hand, Papertrail does not provide built-in alerting features. Although it can integrate with external services for alerting, it requires additional configuration and setup.
Log Management: Papertrail specializes in log management and offers powerful search and filtering capabilities. It allows users to aggregate logs from multiple sources and provides advanced searching options like keyword search, field-based search, and time-range searching. Users can also apply filters to narrow down the search results. Grafana, on the other hand, is not primarily focused on log management. While it can visualize logs, it may not offer the same level of log management functionality as Papertrail.
Ease of Setup and Use: Grafana provides a user-friendly interface and is relatively easy to set up. It offers a comprehensive documentation and a large community, which makes it easier for users to understand and get started with the tool. Grafana also provides many pre-built dashboards and plugins, which can be readily used to monitor and visualize different metrics. Papertrail, on the other hand, is a fully-managed service and requires minimal setup. It provides a simple and intuitive interface, making it easy for users to navigate and search logs without the need for complex configurations.
Pricing: Grafana is an open-source tool and can be used for free. However, it requires infrastructure and resources to set up and maintain. Depending on the data sources and scale, additional costs may be involved. Papertrail, on the other hand, follows a subscription-based pricing model. It offers different pricing plans based on the log volume and retention requirements. While small usage tiers may be available for free, higher usage and additional features may require a paid plan.
In summary, Grafana is a versatile analytics platform focused on data visualization and dashboarding, with support for various databases and extensive customization options. Papertrail, on the other hand, is a cloud-based log management service that emphasizes search and filtering capabilities. The choice between the two depends on specific requirements, including the need for log management, alerting, ease of setup, and pricing considerations.
Looking for a tool which can be used for mainly dashboard purposes, but here are the main requirements:
- Must be able to get custom data from AS400,
- Able to display automation test results,
- System monitoring / Nginx API,
- Able to get data from 3rd parties DB.
Grafana is almost solving all the problems, except AS400 and no database to get automation test results.
You can look out for Prometheus Instrumentation (https://prometheus.io/docs/practices/instrumentation/) Client Library available in various languages https://prometheus.io/docs/instrumenting/clientlibs/ to create the custom metric you need for AS4000 and then Grafana can query the newly instrumented metric to show on the dashboard.
We're looking for a Monitoring and Logging tool. It has to support AWS (mostly 100% serverless, Lambdas, SNS, SQS, API GW, CloudFront, Autora, etc.), as well as Azure and GCP (for now mostly used as pure IaaS, with a lot of cognitive services, and mostly managed DB). Hopefully, something not as expensive as Datadog or New relic, as our SRE team could support the tool inhouse. At the moment, we primarily use CloudWatch for AWS and Pandora for most on-prem.
this is quite affordable and provides what you seem to be looking for. you can see a whole thing about the APM space here https://www.apmexperts.com/observability/ranking-the-observability-offerings/
I worked with Datadog at least one year and my position is that commercial tools like Datadog are the best option to consolidate and analyze your metrics. Obviously, if you can't pay the tool, the best free options are the mix of Prometheus with their Alert Manager and Grafana to visualize (that are complementary not substitutable). But I think that no use a good tool it's finally more expensive that use a not really good implementation of free tools and you will pay also to maintain its.
From a StackShare Community member: “We need better analytics & insights into our Elasticsearch cluster. Grafana, which ships with advanced support for Elasticsearch, looks great but isn’t officially supported/endorsed by Elastic. Kibana, on the other hand, is made and supported by Elastic. I’m wondering what people suggest in this situation."
For our Predictive Analytics platform, we have used both Grafana and Kibana
- Grafana based demo video: https://www.youtube.com/watch?v=tdTB2AcU4Sg
- Kibana based reporting screenshot: https://imgur.com/vuVvZKN
Kibana has predictions and ML algorithms support, so if you need them, you may be better off with Kibana . The multi-variate analysis features it provide are very unique (not available in Grafana).
For everything else, definitely Grafana . Especially the number of supported data sources, and plugins clearly makes Grafana a winner (in just visualization and reporting sense). Creating your own plugin is also very easy. The top pros of Grafana (which it does better than Kibana ) are:
- Creating and organizing visualization panels
- Templating the panels on dashboards for repetetive tasks
- Realtime monitoring, filtering of charts based on conditions and variables
- Export / Import in JSON format (that allows you to version and save your dashboard as part of git)
I use both Kibana and Grafana on my workplace: Kibana for logging and Grafana for monitoring. Since you already work with Elasticsearch, I think Kibana is the safest choice in terms of ease of use and variety of messages it can manage, while Grafana has still (in my opinion) a strong link to metrics
After looking for a way to monitor or at least get a better overview of our infrastructure, we found out that Grafana (which I previously only used in ELK stacks) has a plugin available to fully integrate with Amazon CloudWatch . Which makes it way better for our use-case than the offer of the different competitors (most of them are even paid). There is also a CloudFlare plugin available, the platform we use to serve our DNS requests. Although we are a big fan of https://smashing.github.io/ (previously dashing), for now we are starting with Grafana .
I use Kibana because it ships with the ELK stack. I don't find it as powerful as Splunk however it is light years above grepping through log files. We previously used Grafana but found it to be annoying to maintain a separate tool outside of the ELK stack. We were able to get everything we needed from Kibana.
Kibana should be sufficient in this architecture for decent analytics, if stronger metrics is needed then combine with Grafana. Datadog also offers nice overview but there's no need for it in this case unless you need more monitoring and alerting (and more technicalities).
@Kibana, of course, because @Grafana looks like amateur sort of solution, crammed with query builder grouping aggregates, but in essence, as recommended by CERN - KIbana is the corporate (startup vectored) decision.
Furthermore, @Kibana comes with complexity adhering ELK stack, whereas @InfluxDB + @Grafana & co. recently have become sophisticated development conglomerate instead of advancing towards a understandable installation step by step inheritance.
I learned a lot from Grafana, especially the issue of data monitoring, as it is easy to use, I learned how to create quick and simple dashboards. InfluxDB, I didn't know any other types of DBMS, I only knew about relational DBMS or not, but the difference was the scalability of both, but with influxDB, I knew how a time series DBMS works and finally, Telegraf, which is from the same company as InfluxDB, as I used the Windows Operating System, Telegraf tools was the first in the industry, in addition, it has complete documentation, facilitating its use, I learned a lot about connections, without having to make scripts to collect the data.
The objective of this work was to develop a system to monitor the materials of a production line using IoT technology. Currently, the process of monitoring and replacing parts depends on manual services. For this, load cells, microcontroller, Broker MQTT, Telegraf, InfluxDB, and Grafana were used. It was implemented in a workflow that had the function of collecting sensor data, storing it in a database, and visualizing it in the form of weight and quantity. With these developed solutions, he hopes to contribute to the logistics area, in the replacement and control of materials.
Pros of Grafana
- Beautiful89
- Graphs are interactive68
- Free57
- Easy56
- Nicer than the Graphite web interface34
- Many integrations26
- Can build dashboards18
- Easy to specify time window10
- Can collaborate on dashboards10
- Dashboards contain number tiles9
- Open Source5
- Integration with InfluxDB5
- Click and drag to zoom in5
- Authentification and users management4
- Threshold limits in graphs4
- Alerts3
- It is open to cloud watch and many database3
- Simple and native support to Prometheus3
- Great community support2
- You can use this for development to check memcache2
- You can visualize real time data to put alerts2
- Grapsh as code0
- Plugin visualizationa0
Pros of Papertrail
- Log search85
- Easy log aggregation across multiple machines43
- Integrates with Heroku43
- Simple interface37
- Backup to S326
- Easy setup, independent of existing logging setup19
- Heroku add-on15
- Command line interface3
- Alerting1
- Good for Startups1
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Cons of Grafana
- No interactive query builder1
Cons of Papertrail
- Expensive2
- External Network Goes Down You Wont Be Logging1
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