Grafana vs. IBM Analytics Engine vs. Redash

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

Incentivized

• Well suited for my big data related project or a static data set analysis especially for uploading huge dataset to the cluster.
• But had some issues with connecting IoT real-time data and feeding to Power BI. It might be my understanding please take it as a mere comment rather than a suggestion.

Incentivized

Redash is well suited to situations where metrics are tracked on daily, weekly and monthly basis. Alerts can be set to emails which helps stakeholders to monitor performance on a frequent basis. It is less appropriate for cases where only dashboards are needed. Redash comes into picture where individuals can query and check data at the same time.

• 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

Incentivized

• Jobs with Spark, Hadoop, or Hive queries are rapidly attained
• Can collect, organize and analyze your data accurately
• You can customize, for example, Spark or Hadoop configuration settings, or Python, R, Scala, or Java libraries.

Incentivized

• Great Query Editor with Autocomplete feature
• Very easy to setup and quickly connect to variety of data sources
• Quick Dashboards with Simple UI which can be easily shareable

Incentivized

• There are some settings which we can't configure from UI (Web Console).
• We've open[ed] up configuration files in command line text editors and manually do the settings e.g. LDAP/SSO configuration.
• In terms of visualization, it's best, but it doesn't support log analysis otherwise it could destroy business of all other visualization tools.

• Easier pricing and plug-and-play like you see with AWS and Azure, it would be nice from a budgeting and billing standpoint, as well as better support for the administration.
• Bundling of the Cloud Object Storage should be included with the Analytics Engine.
• The inability to add your own Hadoop stack components has made some transfers a little more complex.

Incentivized

• You need to have a good command over SQL to use Redash but if there could be some way where people can just pull data and do slice dice.
• It would be nice to have an excel kind of filters when all data is fetched.
• Some things like easy to customise the column names.

Incentivized

It is infinitely flexible. If you can imagine it, Grafana can almost certainly do it. Usability may be in the eye of the beholder however, as there is time needed to curate the experience and get the dashboards customized to how it makes sense to you. I know one thing they are working on are more templates, based on data sources

Incentivized

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.

Incentivized

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 no-brainer. As previously stated, the support received was not quite what we expected, but was adequate.

Incentivized

I was not a part of the decision-making team who decided to go with Redash.

Incentivized

• Grafana has replaced many higher priced tools
• The integrations are seemless with multiple backends
• Combining graphs and dashboards from multiple data sources is a game changer

Incentivized

• This product has allowed us to gather analytics data across multiple platforms so we can view and analyze the data from different workflows, all in one place.
• IBM Analytics has allowed us to scale on demand which allows us to capture more and more data, thus increasing our ROI.
• The convenience of the ability to access and administer the product via multiple interfaces has allowed our administrators to ensure that the application is making a positive ROI for our business users and partners.

Incentivized

• Cost effective
• One tool for multiple purpose
• Easy access provision