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Logging · head to head

Datadog Logs vs Apache Spark MLlib

Datadog Logs logo

Datadog Logs

Logging

Log Management and Analytics

From
$0.1/per GB ingested per month
Rated
-
Full reviewWebsite
Apache Spark MLlib logo

Apache Spark MLlib

Machine Learning

Scalable machine learning on Apache Spark

From
Free
Rated
-
Full reviewWebsite

The short version

  • Only Apache Spark MLlib has a free tier, so it costs nothing to try first.
  • Each has a real cost: Datadog Logs complex, multi-tiered pricing model based on ingestion, indexing, and storage; can become expensive at scale; Apache Spark MLlib apache Spark MLlib is Apache 2.0 licensed and free with no paid tier from the Apache project itself; SLA-backed support has to be sourced from a third party such as a managed Spark vendor rather than from Apache.
  • They diverge on capability: Datadog Logs covers Log ingestion, Apache Spark MLlib covers Classification.

Where they differ

Only the attributes on which Datadog Logs and Apache Spark MLlib actually diverge.

Attributes where Datadog Logs and Apache Spark MLlib differ
AttributeDatadog LogsApache Spark MLlib
Starting price$0.1/per GB ingested per monthFree
Pricing modelusage-basedopen-source
Free tierNoYes
PlatformsCloud (AWS, Azure, Google Cloud, Oracle Cloud)Linux, macOS, Windows
CategoryLoggingMachine Learning
Founded20101999

Identical on both: user rating (Not yet rated).

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 Datadog Logs

  • Log ingestion
  • Full-text search
  • Custom dashboards
  • Log-based metrics
  • API
  • Webhooks
  • REST
  • Web support

Only in Apache Spark MLlib

  • Classification
  • Regression
  • Clustering
  • Collaborative filtering
  • Feature engineering
  • Apache Spark
  • Hadoop
  • Kafka

What people use each for

The jobs each tool is most often brought in to do.

Datadog Logs

  • Centralised log aggregation and analysisnot Apache Spark MLlib
  • Multi-source log correlation with metrics and tracesnot Apache Spark MLlib
  • Root cause analysis and troubleshootingnot Apache Spark MLlib
  • Security monitoring and threat detectionnot Apache Spark MLlib

Apache Spark MLlib

  • Machine learningnot Datadog Logs
  • Data sciencenot Datadog Logs
  • Distributed computingnot Datadog Logs

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Datadog Logs

  • Complex, multi-tiered pricing model based on ingestion, indexing, and storage; can become expensive at scale
  • Ingestion pricing of $0.10/GB can accumulate rapidly for high-volume logging environments

Apache Spark MLlib

  • Apache Spark MLlib is Apache 2.0 licensed and free with no paid tier from the Apache project itself; SLA-backed support has to be sourced from a third party such as a managed Spark vendor rather than from Apache.

Pricing, plan by plan

Datadog Logs

$0.1/per GB ingested per month

No published plan breakdown. See the Datadog Logs review.

Apache Spark MLlib

Free

No published plan breakdown. See the Apache Spark MLlib review.

Which should you pick?

Choose Datadog Logs if

  • You need log ingestion.
  • You work on Cloud (AWS, Azure, Google Cloud, Oracle Cloud).
  • You also want full-text search.
Datadog Logs review

Choose Apache Spark MLlib if

  • You need classification.
  • You want to start without paying.
  • You work on Linux, macOS, Windows.
  • You also want regression.
Apache Spark MLlib review

Questions people ask

Is Datadog Logs or Apache Spark MLlib better?
Neither clearly leads. Datadog Logs starts at $0.1/per GB ingested per month and Apache Spark MLlib at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Datadog Logs or Apache Spark MLlib?
Apache Spark MLlib has a free tier; the other does not. Paid plans start at $0.1/per GB ingested per month for Datadog Logs and Free for Apache Spark MLlib.
Does Datadog Logs or Apache Spark MLlib run on more platforms?
Datadog Logs runs on Cloud (AWS, Azure, Google Cloud, Oracle Cloud). Apache Spark MLlib runs on Linux, macOS, Windows.
Can I use Apache Spark MLlib for free?
Yes. Apache Spark MLlib has a free tier, so you can try it without paying. Datadog Logs starts at $0.1/per GB ingested per month.
What is Datadog Logs best used for?
Datadog Logs is most often used for centralised log aggregation and analysis, multi-source log correlation with metrics and traces, root cause analysis and troubleshooting, security monitoring and threat detection. Of those, centralised log aggregation and analysis and multi-source log correlation with metrics and traces are not what Apache Spark MLlib is typically brought in for.
What can Datadog Logs do that Apache Spark MLlib cannot?
Datadog Logs covers Log ingestion, Full-text search, Custom dashboards, Log-based metrics. Apache Spark MLlib covers Classification, Regression, Clustering, Collaborative filtering.

Answered from the vendors’ own pages

Datadog Logs: What pricing options does Datadog offer for log ingestion and processing?

Log ingestion starts at $0.10/GB (annual billing; $0.10 on-demand). Standard indexing costs $1.70 per million events per month (annual; $2.55 on-demand). Flex Storage costs $0.05/million events stored per month (annual; $0.075 on-demand). Flex Logs Starter costs $0.60/million events stored per month (annual; $0.90 on-demand).

Source
Apache Spark MLlib: How much does Apache Spark MLlib cost?

MLlib is completely free and open source, licensed under the Apache License Version 2.0. There are no subscription, licensing, or usage fees.

Source
Datadog Logs: What retention options are available and how does it affect pricing?

Standard indexing offers 15-day retention with options for 3 to 30+ days. Flex Storage supports flexible retention up to 15 months. Flex Logs Starter includes bundled compute for retention of 3-15 months.

Source
Apache Spark MLlib: What licensing does MLlib use?

MLlib is licensed under Apache License Version 2.0, making it freely available for all users regardless of organization size or use case.

Source
Datadog Logs: Is there a cost to forward logs to external systems?

Yes, log forwarding costs $0.25/GB outbound per destination for routing logs to external systems.

Source
Apache Spark MLlib: How do I use MLlib?

MLlib is built into Apache Spark. Download Spark, which includes MLlib as a module, and deploy on your choice of infrastructure including Hadoop, Mesos, Kubernetes, standalone, or cloud.

Source
Datadog Logs: What discounts are available for high-volume customers?

Multi-year and volume discounts are available for customers processing 3B+ events per month.

Source
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