Kibana vs. Logstash

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Kibana
Score 8.1 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
Logstash
Score 7.6 out of 10
N/A
N/AN/A
Pricing
KibanaLogstash
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
KibanaLogstash
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Features
KibanaLogstash
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
Kibana
9.0
5 Ratings
7% above category average
Logstash
-
Ratings
Pixel Perfect reports9.02 Ratings00 Ratings
Customizable dashboards9.05 Ratings00 Ratings
Report Formatting Templates9.03 Ratings00 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
Logstash
-
Ratings
Drill-down analysis7.05 Ratings00 Ratings
Formatting capabilities7.04 Ratings00 Ratings
Report sharing and collaboration3.04 Ratings00 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
Logstash
-
Ratings
Publish to Web9.52 Ratings00 Ratings
Publish to PDF8.52 Ratings00 Ratings
Report Versioning9.01 Ratings00 Ratings
Report Delivery Scheduling9.01 Ratings00 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
Logstash
-
Ratings
Pre-built visualization formats (heatmaps, scatter plots etc.)7.04 Ratings00 Ratings
Location Analytics / Geographic Visualization9.52 Ratings00 Ratings
Predictive Analytics10.01 Ratings00 Ratings
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KibanaLogstash
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User Ratings
KibanaLogstash
Likelihood to Recommend
7.0
(5 ratings)
10.0
(3 ratings)
Support Rating
7.7
(2 ratings)
-
(0 ratings)
User Testimonials
KibanaLogstash
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.
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Elastic
Perfect for projects where Elasticsearch makes sense: if you decide to employ ES in a project, then you will almost inevitably use LogStash, and you should anyways. Such projects would include: 1. Data Science (reading, recording or measure web-based Analytics, Metrics) 2. Web Scraping (which was one of our earlier projects involving LogStash) 3. Syslog-ng Management: While I did point out that it can be a bit of an electric boo-ga-loo in finding an errant configuration item, it is still worth it to implement Syslog-ng management via LogStash: being able to fine-tune your log messages and then pipe them to other sources, depending on the data being read in, is incredibly powerful, and I would say is exemplar of what modern Computer Science looks like: Less Specialization in mathematics, and more specialization in storing and recording data (i.e. Less Engineering, and more Design).
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Pros
Elastic
  • Fast searches with powerful index.
  • Beautiful data visualizations.
  • Real-time observability.
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Elastic
  • Logstash design is definitely perfect for the use case of ELK. Logstash has "drivers" using which it can inject from virtually any source. This takes the headache from source to implement those "drivers" to store data to ES.
  • Logstash is fast, very fast. As per my observance, you don't need more than 1 or 2 servers for even big size projects.
  • Data in different shape, size, and formats? No worries, Logstash can handle it. It lets you write simple rules to programmatically take decisions real-time on data.
  • You can change your data on the fly! This is the CORE power of Logstash. The concept is similar to Kafka streams, the difference being the source and destination are application and ES respectively.
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Cons
Elastic
  • Some performance issues with large datasets.
  • Linking to dashboards makes extremely long urls.
  • Lack of reports.
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Elastic
  • Since it's a Java product, JVM tuning must be done for handling high-load.
  • The persistent queue feature is nice, but I feel like most companies would want to use Kafka as a general storage location for persistent messages for all consumers to use. Using some pipeline of "Kafka input -> filter plugins -> Kafka output" seems like a good solution for data enrichment without needing to maintain a custom Kafka consumer to accomplish a similar feature.
  • I would like to see more documentation around creating a distributed Logstash cluster because I imagine for high ingestion use cases, that would be necessary.
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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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Elastic
No answers on this topic
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.
Read full review
Elastic
MongoDB and Azure SQL Database are just that: Databases, and they allow you to pipe data into a database, which means that alot of the log filtering becomes a simple exercise of querying information from a DBMS. However, LogStash was chosen for it's ease of integration into our choice of using ELK Elasticsearch is an obvious inclusion: Using Logstash with it's native DevOps stack its really rational
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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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Elastic
  • Positive: Learning curve was relatively easy for our team. We were up and running within a sprint.
  • Positive: Managing Logstash has generally been easy. We configure it, and usually, don't have to worry about misbehavior.
  • Negative: Updating/Rehydrating Logstash servers have been little challenging. We sometimes even loose data while Logstash is down. It requires more in-depth research and experiments to figure the fine-grained details.
  • Negative: This is now one more application/skill/server to manage. Like any other servers, it requires proper grooming or else you will get in trouble. This is also a single point of failure which can have the ability to make other servers useless if it is not running.
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ScreenShots