Grafana Loki vs. Logstash

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Grafana Loki
Score 8.7 out of 10
N/A
Grafana Logs (powered by Loki) brings together logs from applications and infrastructure in a single place. By using the exact same service discovery and label model as Prometheus, Grafana Logs can systematically guarantee logs have consistent metadata with metrics. Grafana Logs lets users send logs in any format, from any source so it’s easy to add to existing infrastructure and get up and running quickly. Leverage a wide array of clients for shipping logs like…
$0
Logstash
Score 7.6 out of 10
N/A
N/AN/A
Pricing
Grafana LokiLogstash
Editions & Modules
No answers on this topic
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Offerings
Pricing Offerings
Grafana LokiLogstash
Free Trial
NoNo
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
YesNo
Entry-level Setup FeeOptionalNo setup fee
Additional Details
More Pricing Information
Community Pulse
Grafana LokiLogstash
Top Pros

No answers on this topic

Top Cons

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Best Alternatives
Grafana LokiLogstash
Small Businesses
SolarWinds Papertrail
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Score 8.8 out of 10
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Score 8.8 out of 10
Medium-sized Companies
SolarWinds Papertrail
SolarWinds Papertrail
Score 8.8 out of 10
SolarWinds Papertrail
SolarWinds Papertrail
Score 8.8 out of 10
Enterprises
Splunk Log Observer
Splunk Log Observer
Score 8.6 out of 10
Splunk Log Observer
Splunk Log Observer
Score 8.6 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Grafana LokiLogstash
Likelihood to Recommend
10.0
(1 ratings)
10.0
(3 ratings)
Likelihood to Renew
10.0
(1 ratings)
-
(0 ratings)
User Testimonials
Grafana LokiLogstash
Likelihood to Recommend
Grafana Labs
In our application there are many points from where logs are coming so in order to go to each and every application and check logs its very overhead so we are using Grafana Loki for the logs gathering and monitoring.
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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
Grafana Labs
  • Access to many open-source dashboards, access to add many data-sources to gather and visualize data from.
  • Grafana Loki does well gathering of logs from various data-sources, we can also filter the logs based on our needs.
  • One stop solution for all the logs and monitoring.
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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
Grafana Labs
  • We can modify the logs directly from UI of Grafana Loki
  • Better and simplified options for logs filtering
  • Easy usability with SMTP configuration and other system level configuration
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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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Alternatives Considered
Grafana Labs
First and foremost if Grafana Loki is based on CNCF open source projects so organizations can get freedom to choice to configure it at your own other main thing is Grafana Loki is totally free of cost and we can deploy it on our infrastructure. On compared with other managed services like Datadog, New Relic it is very expensive and we also don't have much control on the tools we use.
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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
Grafana Labs
  • Only indexes the metadata
  • Have to manage it by ourselves compare to other available managed monitoring and log observability solutions
  • Dedicated person or team of SRE to manage the monitoring and observability solutions
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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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