Grafana vs. IBM Analytics Engine

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Grafana
Score 8.7 out of 10
N/A
Grafana is a data visualization tool developed by Grafana Labs in New York. It is available open source, managed (Grafana Cloud), or via an enterprise edition with enhanced features. Grafana has pluggable data source model and comes bundled with support for popular time series databases like Graphite. It also has built-in support for cloud monitoring vendors like Amazon Cloudwatch, Microsoft Azure and SQL databases like MySQL. Grafana can combine data from many places into a single dashboard.
$8
per month up to 1 active user
IBM Analytics Engine
Score 7.1 out of 10
N/A
IBM BigInsights is an analytics and data visualization tool leveraging hadoop.N/A
Pricing
GrafanaIBM Analytics Engine
Editions & Modules
Grafana Cloud - Pro
$8
per month up to 1 active user
Grafana Cloud - Free
Free
10k metrics + 50GB logs + 50GB traces up to 3 active users
Grafana Cloud - Advanced
Volume Discounts
custom data usage custom active users
Grafana - Enterprise Stack
Custom Pricing
No answers on this topic
Offerings
Pricing Offerings
GrafanaIBM Analytics Engine
Free Trial
YesNo
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
GrafanaIBM Analytics Engine
Considered Both Products
Grafana
Chose Grafana
Easy to use
Easy to configure
Cost efficient
Chose Grafana
Grafana is more flexible, readily adopts other tools frameworks instead of forcing you to use their agent, doesn't force you into Vendor lock-in, and embraces open source, self-hosted, and Enterprise. Similar companies would like you to use their specific tooling and don't …
Chose Grafana
Grafana gives more flexibility to explore its features. A new user can explore experiment and work with free Grafana account and find if it is suitable for them.Other platforms don't have the features in their freemium version that Grafana has. It lets us try features of …
Chose Grafana
Grafana has a direct plugin to Icinga monitoring solution and allowed for easy configuration for us. At the time of implementation, other services did not have such an integration. As we already had a very customized and heavily introduced monitoring solution in place, we …
Chose Grafana
Grafana blows Nagios out of the water when it comes to customization. The ability to feed almost any data source makes it very versatile and the cost is great.
IBM Analytics Engine
Chose IBM Analytics Engine
We have tried the following solutions in the past and I must say they can't compare to IBM Analytics Engine:

Chose IBM Analytics Engine
Our data analytics team happened to try IBM Analytics just to get acquainted with it & it turned out that this tool fits our business requirement better than the one which we were using in terms of the features along with the level of support that they provide. so, choosing the …
Chose IBM Analytics Engine
IBM Analytics is a great tool and a welcome addition to your overall IBM strategy. I think in cases of tools like this, you either go with what your platform works best with or you go completely different with a 3rd party, like Snowflake. We are an Azure shop and just happened …
Chose IBM Analytics Engine
We initially wanted to go with Google BigQuery, mainly for the name recognition. However, the pricing and support structure led us to seek alternatives, which pointed us to IBM. Apache Spark was also in the running, but here IBM's domination in the industry made the choice a …
Chose IBM Analytics Engine
We did an evaluation of Google Analytics and Microsoft Azure Stream Analytics in comparison to the IBM Analytics Engine product. We choose the product offering from IBM because we felt that for our company, this product offered a more complete and comprehensive package to …
Chose IBM Analytics Engine
Hortonworks Data Platform, Apache Spark, Tableau Desktop and Tableau Online
Chose IBM Analytics Engine
  • I have been using Azure for my previous analysis, I had a difficult time in understanding the Analytics engine rather IBM provided step by step tutorial for setup.
  • Also turning off a machine was not an option in Azure for some of the services so I had to pay for the service …
Chose IBM Analytics Engine
Our professor has worked with IBM And many major tech companies. He’d recommend us which tools to use. And comparing to Azure, IBM is more convenient to use.
Features
GrafanaIBM Analytics Engine
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
Grafana
8.0
Ratings
5% below category average
IBM Analytics Engine
-
Ratings
Pixel Perfect reports6.00 Ratings00 Ratings
Customizable dashboards10.00 Ratings00 Ratings
Report Formatting Templates8.00 Ratings00 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
Grafana
6.8
Ratings
16% below category average
IBM Analytics Engine
-
Ratings
Drill-down analysis6.00 Ratings00 Ratings
Formatting capabilities8.00 Ratings00 Ratings
Integration with R or other statistical packages5.10 Ratings00 Ratings
Report sharing and collaboration8.00 Ratings00 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
Grafana
8.4
Ratings
0% below category average
IBM Analytics Engine
-
Ratings
Publish to Web7.00 Ratings00 Ratings
Publish to PDF9.00 Ratings00 Ratings
Report Versioning9.00 Ratings00 Ratings
Report Delivery Scheduling8.00 Ratings00 Ratings
Delivery to Remote Servers9.00 Ratings00 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
Grafana
7.7
Ratings
6% below category average
IBM Analytics Engine
-
Ratings
Pre-built visualization formats (heatmaps, scatter plots etc.)9.00 Ratings00 Ratings
Location Analytics / Geographic Visualization9.00 Ratings00 Ratings
Predictive Analytics7.00 Ratings00 Ratings
Pattern Recognition and Data Mining6.00 Ratings00 Ratings
Best Alternatives
GrafanaIBM Analytics Engine
Small Businesses
Supermetrics
Supermetrics
Score 10.0 out of 10

No answers on this topic

Medium-sized Companies
Supermetrics
Supermetrics
Score 10.0 out of 10
Cloudera Manager
Cloudera Manager
Score 9.9 out of 10
Enterprises
Dataiku
Dataiku
Score 7.6 out of 10
Apache Spark
Apache Spark
Score 9.2 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
GrafanaIBM Analytics Engine
Likelihood to Recommend
9.0
(0 ratings)
9.5
(0 ratings)
Usability
10.0
(0 ratings)
-
(0 ratings)
User Testimonials
GrafanaIBM Analytics Engine
Likelihood to Recommend
Just about any organization with more than one server and more than one cluster as it scales very well. Configuration of the application takes time and finesse to fine tune to where the balance of load time and getting data quickly meets. The plugins add load time but fine tuning for the application to meet demand needs nailed down at implementation
Read full review
We are at present utilizing IBM Analytics Engine and it works incredible. Following are the things that I like the most about this product is:- - Simple to Utilize - Reasonable Cost - With only a couple seconds you can ready to fabricate and convey groups - you can without much of a stretch break down information through different applications
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Pros
  • Alerting through many different medium as Slack, Email, Webhook etc
  • Beautiful and unlimited number of dashboards to view your metrics and tweak them as you please
  • Log aggregation and powerful Logql to filter and view your logs
  • Microservices monitoring
  • Large number of plugins and data sources to collect your metrics from almost anywhere
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  • We are able to build and deploy clusters within minutes to simplify user experience and increase scalability and reliability.
  • We are able to scale and compute on-demand to handle newer workloads like machine learning.
  • We really like that we are able to access and administer the application via multiple interfaces.
Read full review
Cons
  • Documentation needs to be more clarified since it can be confusing for beginners
  • Notification alert message templates need to be simplified
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  • I would like to see a more robust version of their online help
  • The speed of their business support is adequate, but I kind of expect more from such a powerhouse.
  • Problems with duration of cluster life
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Usability
Great usage in terms of monitoring of any application from backend to frontend and even any AWS resource via cloud watch and other connectors. Easy to use and configure personalised dash boarding and alerting features. Cost efficient and easy to setup and run, no mazor scaling challenges in terms of managing and maintaining the stack, easy to configure via Prometheus, influx and other connectors
Read full review
No answers on this topic
Alternatives Considered
Grafana is more flexible, readily adopts other tools frameworks instead of forcing you to use their agent, doesn't force you into Vendor lock-in, and embraces open source, self-hosted, and Enterprise. Similar companies would like you to use their specific tooling and don't offer nearly as much flexibility. The other thing I like about Grafana is their storage usage is much lower compared to similar tools and competitors
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  • I have been using Azure for my previous analysis, I had a difficult time in understanding the Analytics engine rather IBM provided step by step tutorial for setup.
  • Also turning off a machine was not an option in Azure for some of the services so I had to pay for the service whether I use it or not
Read full review
Return on Investment
  • It has kicked out some of our paid monitoring and visualization tools.
  • Now Monitoring, Visualization and Alerting is being done in a single platform.
  • It made monitoring and visualization very easy for us.
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  • It has saved us quite a bit of time managing our catalog of clusters and keeping things organized.
  • Since we had a division we acquired running IBM Cloud, it was easy to get it running and try it out, but we found we prefer our Azure configuration better simply to keep our technology in alignment across corporate functions.
  • I definitely see some cost savings by separating out the storage and compute. It helps you start to put an appropriate price tag on certain instances of big data.
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ScreenShots