Kibana allows users to visualize Elasticsearch data and navigate the Elastic Stack so you can do anything from tracking query load to understanding the way requests flow through your apps.
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Sigma
Score 9.1 out of 10
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Sigma Computing headquartered in San Francisco provides a suite of data services such as code free data modeling, data search and explorating, and related BI and data visualization services.
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Pricing
Kibana
Sigma Computing
Editions & Modules
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No answers on this topic
Offerings
Pricing Offerings
Kibana
Sigma
Free Trial
No
Yes
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
Optional
Additional Details
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More Pricing Information
Community Pulse
Kibana
Sigma Computing
Features
Kibana
Sigma Computing
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
Kibana
9.0
Ratings
7% above category average
Sigma Computing
8.9
Ratings
9% above category average
Pixel Perfect reports
9.00 Ratings
8.80 Ratings
Customizable dashboards
9.00 Ratings
9.20 Ratings
Report Formatting Templates
9.00 Ratings
8.70 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
Kibana
5.7
Ratings
33% below category average
Sigma Computing
8.6
Ratings
7% above category average
Drill-down analysis
7.00 Ratings
9.40 Ratings
Formatting capabilities
7.00 Ratings
8.30 Ratings
Report sharing and collaboration
3.00 Ratings
9.40 Ratings
Integration with R or other statistical packages
00 Ratings
7.30 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
Kibana
8.8
Ratings
4% above category average
Sigma Computing
9.1
Ratings
9% above category average
Publish to Web
9.50 Ratings
9.90 Ratings
Publish to PDF
8.50 Ratings
9.00 Ratings
Report Versioning
9.00 Ratings
9.90 Ratings
Report Delivery Scheduling
9.00 Ratings
9.80 Ratings
Delivery to Remote Servers
8.00 Ratings
7.00 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
Great for teams big and small that want a single pane of glass for understanding their systems, from dev, to staging, to production. Well-suited for teams that need to preserve logs for long-term compliance reasons, and also mine their logs for useful operational insights. Highly recommended as both an open source project and a commercial offering with fantastic paid support.
Scenarios where Sigma Computing is well suited: - Data Reporting and Visualisation : It is suitable for dashboards that integrate data from multiple back-office systems - Search and Filtering Capabilities: It provides a robust platform for searching through datasets and visualisations. Scenarios where Sigma Computing is less appropriate: Handling of null values and dynamic table adjustments
Viewer level license is quite limited. These users can't download data or even add filters on datasets. Something to keep in mind.
Directly querying the underlying data warehouse will lead to increased usage. Not a big deal on something like Redshift, but your Snowflake consumption will increase, potentially by a lot.
Because we are very satisfied with the product and would most likely renew because of the services it provides. It is a tool that you bring into your organization and let it change the way you analyze your data, present your data and share you date within the Respective teams
Its usability is generally good and it provides teams with a basic to intermediate understanding about data visualization. It is very user-friendly when it comes to creating dashboards. The UI is very good and simple. Its integration with other tools for alerting and reporting is amazing. But its advance features have a learning curve and a first timer needs some time to use the advance features.
It has a clean and modern interface. However, it is not completely intuitive. I think it would be better and easier to navigate with more Windows style drop down menus and/or tabls. There is a significant learning curve, but that may be due in part to the technical nature of this type of software tool.
They are very friendly and informative. They are quick in resolving our queries and help us understand very minute things as well. They are quick in creating feature tickets based on our custom requirements, and they would also create a bug ticket if there is any discrepancy and get that checked on time.
Well when it comes to using Kibana when compared to Datadog, I can say that Kibana is pretty [...] cheap. Apart from APM and Datadog hosted agents, Kibana gives a good competition to Datadog for real time log analysis as well as metrics analysis. While OpsGenie is a great tool for alerting, it lacks visualization when compared to Kibana. Grafana is another opensource tool that gives a lot of insights like Kibana but Grafana cannot be easily integrated with OpenSearch.
I am not an expert in any of these, though from my brief exposure to Looker it felt like a steeper learning curve, more appropriate to companies with dedicated and skilled BI engineers, whereas Sigma (and Tableau, and Looker Studio) offer a quicker and more intuitive interface for smaller companies like ours without dedicated BI resources on staff.
Monitoring health of cloud platform has allowed the company to anticipate issues before they affect customers – Sigma prompted us building a canary monitoring process that provides customer container health.
Customer success has used an activity report to discover customers running runaway processes that they were unaware of, creating an alert to contact the customer and prevent an embarrassing situation.
Customer success uses the activity report to prompt conversations regarding increases or declines in behavior that led to increasing contract limits or addressing churn concerns.
