Software · head to head
Fluentd vs Loki
The short version
- Each has a real cost: Fluentd fluentd needs more than 60 MB of memory at runtime, against roughly 450 KB for Fluent Bit; Loki the Grafana Cloud free tier caps log ingestion at 50 GB a month with 14 day retention
- They diverge on capability: Fluentd covers Log collection, Loki covers Log aggregation.
Where they differ
Only the attributes on which Fluentd and Loki actually diverge.
Identical on both: starting price (Free), pricing model (open-source), free tier (Yes), platforms (Web, Api), user rating (Not yet rated), category (Unknown).
What each one covers
Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.
Only in Fluentd
- Log collection
- Data parsing
- Filtering and buffering
- Event routing
Only in Loki
- Log aggregation
- Label-based indexing
- Real-time log streaming
- LogQL query language
Both cover
- API
- Webhooks
- REST
- Web support
- Api support
What people use each for
The jobs each tool is most often brought in to do.
Fluentd
- Unified log collection and routing from many sources to many destinationsnot Loki
- Parsing and transforming log records before forwardingnot Loki
- Aggregating logs from containers into Elasticsearch, S3 or a SIEMnot Loki
Loki
- Aggregating application and infrastructure logs with label based indexingnot Fluentd
- Querying logs alongside metrics in Grafananot Fluentd
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Fluentd
- Fluentd needs more than 60 MB of memory at runtime, against roughly 450 KB for Fluent Bit
- Fluentd is built as a Ruby gem and depends on other gems, so a Ruby runtime is required
- Its capability comes from over 1,000 external plugins rather than built in functionality, so each added input or output is a separate dependency
- The Fluent Bit documentation states that cloud providers have switched from Fluentd to Fluent Bit for performance and compatibility and calls Fluent Bit the next generation solution
Loki
- The Grafana Cloud free tier caps log ingestion at 50 GB a month with 14 day retention
- Paid log pricing is split across three separate meters, at $0.050 per GB processed, $0.400 per GB written and $0.100 per GB retained
- Retaining logs is billed separately from ingesting them, so keeping data costs on an ongoing basis rather than once
- The Pro plan carries a $19 a month platform fee before any usage charges
Pricing, plan by plan
Fluentd
Free- FreeFree
- Log collection
- Data parsing
- Filtering and buffering
Loki
Free- FreeFree
- Log aggregation
- Label-based indexing
- Real-time log streaming
Which should you pick?
Choose Fluentd if
- You need log collection.
- You want to start without paying.
- You work on Web, Api.
- You also want data parsing.
Choose Loki if
- You need log aggregation.
- You want to start without paying.
- You work on Web, Api.
- You also want label-based indexing.
Questions people ask
- Is Fluentd or Loki better?
- Neither clearly leads. Fluentd starts at Free and Loki at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Fluentd or Loki?
- Fluentd starts at Free and Loki at Free.
- Does Fluentd or Loki run on more platforms?
- Both run on Web, Api, so platform support will not decide this one for you.
- Can I use Fluentd for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Fluentd best used for?
- Fluentd is most often used for unified log collection and routing from many sources to many destinations, parsing and transforming log records before forwarding, aggregating logs from containers into elasticsearch, s3 or a siem. Of those, unified log collection and routing from many sources to many destinations and parsing and transforming log records before forwarding are not what Loki is typically brought in for.
- What can Fluentd do that Loki cannot?
- Fluentd covers Log collection, Data parsing, Filtering and buffering, Event routing. Loki covers Log aggregation, Label-based indexing, Real-time log streaming, LogQL query language. Both handle API, Webhooks, REST, Web support.
Related pages
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