Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Kibana
Score 8.0 out of 10
N/A
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.N/A
Looker
Score 8.2 out of 10
N/A
Looker is a BI application with an analytics-oriented application server that sits on top of relational data stores. It includes an end-user interface for exploring data, a reusable development paradigm for data discovery, and an API for supporting data in other systems.N/A
Pricing
KibanaLooker
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
KibanaLooker
Free Trial
NoYes
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoYes
Entry-level Setup FeeNo setup feeRequired
Additional DetailsMust contact sales team for pricing.
More Pricing Information
Features
KibanaLooker
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
Kibana
9.0
5 Ratings
7% above category average
Looker
8.1
97 Ratings
1% below category average
Pixel Perfect reports9.02 Ratings7.680 Ratings
Customizable dashboards9.05 Ratings8.896 Ratings
Report Formatting Templates9.03 Ratings7.982 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
Kibana
5.7
5 Ratings
34% below category average
Looker
8.1
97 Ratings
0% above category average
Drill-down analysis7.05 Ratings8.294 Ratings
Formatting capabilities7.04 Ratings7.495 Ratings
Report sharing and collaboration3.04 Ratings8.697 Ratings
Integration with R or other statistical packages00 Ratings8.040 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
Kibana
8.8
2 Ratings
5% above category average
Looker
8.6
93 Ratings
3% above category average
Publish to Web9.52 Ratings8.577 Ratings
Publish to PDF8.52 Ratings8.783 Ratings
Report Versioning9.01 Ratings8.263 Ratings
Report Delivery Scheduling9.01 Ratings8.983 Ratings
Delivery to Remote Servers8.01 Ratings00 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
Kibana
8.8
4 Ratings
7% above category average
Looker
6.8
94 Ratings
17% below category average
Pre-built visualization formats (heatmaps, scatter plots etc.)7.04 Ratings8.192 Ratings
Location Analytics / Geographic Visualization9.52 Ratings7.581 Ratings
Predictive Analytics10.01 Ratings4.66 Ratings
Access Control and Security
Comparison of Access Control and Security features of Product A and Product B
Kibana
-
Ratings
Looker
8.5
93 Ratings
0% below category average
Multi-User Support (named login)00 Ratings8.988 Ratings
Role-Based Security Model00 Ratings8.381 Ratings
Multiple Access Permission Levels (Create, Read, Delete)00 Ratings8.688 Ratings
Report-Level Access Control00 Ratings8.429 Ratings
Mobile Capabilities
Comparison of Mobile Capabilities features of Product A and Product B
Kibana
-
Ratings
Looker
5.8
69 Ratings
31% below category average
Responsive Design for Web Access00 Ratings6.766 Ratings
Mobile Application00 Ratings5.01 Ratings
Dashboard / Report / Visualization Interactivity on Mobile00 Ratings6.560 Ratings
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User Ratings
KibanaLooker
Likelihood to Recommend
7.0
(5 ratings)
8.4
(98 ratings)
Likelihood to Renew
-
(0 ratings)
9.0
(4 ratings)
Usability
-
(0 ratings)
8.8
(12 ratings)
Support Rating
7.7
(2 ratings)
8.8
(14 ratings)
User Testimonials
KibanaLooker
Likelihood to Recommend
Elastic
Kibana integrates seamlessly with Elastic Search which gives us access to parse and analyze data generated from our systems in order to make decisions. Also, Kibana helps us create insightful reports and dashboards that give us insights into the end-users usage on the system and helps us find the root cause of issues as well.
Read full review
Google
Quick dashboards from Google Sheets - Easier to do the graphs than in Google Sheets - Operational dashboards to be used in the day-to-day work - It is good both for retrospective data and to do a pulse check of the current status - Better for not giant amounts of data and not multiple data sources. - If you need a lot of graphs to be displayed on the same page, it can be a bit glitchy during configuration (then the use works fine).
Read full review
Pros
Elastic
  • Fast searches with powerful index.
  • Beautiful data visualizations.
  • Real-time observability.
Read full review
Google
  • Filtering - you can filter across different dimensions and metrics to get a more specific "cut" of data
  • Refreshing - data automatically ingests into Looker which allows reports to be updated and backfilled in real time
  • Conditional Reporting - you can leverage Looker's reporting features to flag when a given metric or KPI falls below or above a specified threshold. For example, if you had a daily sales benchmark in a SAAS organization, you could use Looker to flag whenever daily sales falls above or below the benchmark
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Cons
Elastic
  • Some performance issues with large datasets.
  • Linking to dashboards makes extremely long urls.
  • Lack of reports.
Read full review
Google
  • Looker is less graphical or pictorial which makes it less attractive
  • Consumes a lot of memory when there are multiple rows and columns, impacts performance too
  • At times when we download huge chunks of raw data from Looker dashbords, the time taken to prepare the file is enormous - The user fails to understand if Looker has frozen or if the data is getting prepared in the background for downloading. In turn, user ends up triggering multiple downloads
Read full review
Likelihood to Renew
Elastic
No answers on this topic
Google
We've been very happy with Looker so far, and all teams in the organization are starting to see its value, and use it on a frequent basis. It has quickly become our accessible "source of truth" for all data/metrics.
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Usability
Elastic
No answers on this topic
Google
Looker is relatively easy to use, even as it is set up. The customers for the front-end only have issues with the initial setup for looker ml creations. Other "looks" are relatively easy to set up, depending on the ETL and the data which is coming into Looker on a regular basis.
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Support Rating
Elastic
We did not use the official Kibana support. Documentation was easy enough to follow.
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Google
Never had to work with support for issues. Any questions we had, they would respond promptly and clearly. The one-time setup was easy, by reading documentation. If the feature is not supported, they will add a feature request. In this case, LDAP support was requested over OKTA. They are looking into it.
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Alternatives Considered
Elastic
Kibana has a better usability experience, the core features I was using existed in all of them. I liked more in Kibana how you can easily create dashboards, charts, and reports without the need to be a tech person.
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Google
Looker is an off-the-shelf, free tool for Google business users. Other than the internal cost of time to build, we had no costs to set up what we needed to do. Knowledge sharing internally and using templates greatly reduced this cost, making the overall cost very low.
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Return on Investment
Elastic
  • Issues that affect checkout experiences for customers are able to be prioritized and solved quickly.
  • We are able to more efficiently use resources due to the automation of reporting alerts. Decreasing employee resources needed.
  • Visualization allows us to quickly share issues and explain to coworkers in order to escalate issues that can cost our bottom line.
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Google
  • Allowing others to self-serve their own analytics and connect it to Looker simply and easily has helped unblock the central data team so they can instead focus on validated dashboards whilst stakeholders manage their day-to-day analysis themselves. Countless engineering hours have been freed up by not having to manage every user permission for each BI tool; we have a BYOBI approach; Bring Your Own BI
  • Creation and management of a semantic layer (LookML =Looker Modeling Language ) allows peoples sandboxes and production databases to become clutter free. Minor adjustments, conditional fields, and even some modelling can all be done in LookML which doesn't need oversight or governance from the central data team.
  • LookML, specifying drilldown fields and their sub-queries, as well as generally creating dynamic parameters with Liquid are all great features, but can have a steep learning curve. it may take some time to understand how to create this middle layer correctly, or even pose a risk of inheriting complex code from another source which can be unmaintainable if it becomes too big. Some level of governance is recommended if Looker is used by a large number of editors.
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ScreenShots

Looker Screenshots

Screenshot of a Looker dashboard with a geo chart.