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Machine Learning · head to head

Comet ML vs PlanetScale

Comet ML logo

Comet ML

Machine Learning

Platform for tracking, comparing, and optimizing ML experiments

From
Free
Rated
-
PlanetScale logo

PlanetScale

Databases

The MySQL-compatible serverless database

From
Free
Rated
-

The short version

  • Each has a real cost: Comet ML the free cloud tier caps data at 25,000 spans a month with 60 day retention; PlanetScale pricing varies significantly across 17+ AWS and GCP regions
  • They diverge on capability: Comet ML covers Experiment tracking, PlanetScale covers Database Branching.

Where they differ

Only the attributes on which Comet ML and PlanetScale actually diverge.

Attributes where Comet ML and PlanetScale differ
AttributeComet MLPlanetScale
Pricing modelfreemiumusage-based
PlatformsWeb, Linux, Mac, WindowsCloud-hosted (AWS, GCP, Azure)
CategoryMachine LearningDatabases
Founded20172018

Identical on both: starting price (Free), free tier (Yes), 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 Comet ML

  • Experiment tracking
  • Code versioning
  • Model registry
  • Hyperparameter optimization
  • Production monitoring
  • PyTorch
  • TensorFlow
  • Keras

Only in PlanetScale

  • Database Branching
  • Non-blocking Schema Changes
  • Insights
  • Horizontal Scaling
  • Connection Pooling
  • Query Caching
  • Automatic Backups
  • Global Replication

Both cover

  • Web support

What people use each for

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

Comet ML

  • LLM observability and monitoringnot PlanetScale
  • AI agent testing and debuggingnot PlanetScale
  • Experiment tracking for machine learningnot PlanetScale
  • Model registry and version managementnot PlanetScale
  • ML model training monitoringnot PlanetScale

PlanetScale

  • MySQL-compatible applications requiring horizontal scalingnot Comet ML
  • PostgreSQL deployments with custom cluster configurationsnot Comet ML
  • Multi-region database deployments on AWS or GCPnot Comet ML
  • Applications requiring transparent sharding via Vitessnot Comet ML

Where each one falls short

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

Comet ML

  • The free cloud tier caps data at 25,000 spans a month with 60 day retention
  • Retention stays at 60 days even on the paid Pro plan, and extending it is a $29 per 100k spans add on
  • Overage on Pro is $5 per additional 100,000 spans
  • The free MLOps tier is a single user with 100 GB of storage and training hours governed by a fair usage policy
  • Pro MLOps is $19 per user per month and caps the team at 10 users

PlanetScale

  • Pricing varies significantly across 17+ AWS and GCP regions
  • Additional costs for EBS storage beyond base tier, backup storage, and egress
  • Dedicated PgBouncer and replicas incur separate charges
  • Metal tier pricing increases sharply with larger configurations

Pricing, plan by plan

Comet ML

Free
  • Free CloudFree
    • Up to 10 team members
    • 25,000 spans per month
    • 60-day data retention
  • Pro Cloud$19/month
    • Up to 50 team members
    • 100,000 spans per month
    • 60-day data retention
  • MLOps FreeFree
    • 1 user with fair usage policy
    • Experiment tracking
    • Dataset management
  • MLOps Pro$19/user/month
    • Up to 10 users
    • 1,500 training hours included
    • 500GB storage included

PlanetScale

Free
  • Postgres EBS Single-Node (ARM64 PS-5)$5/month
    • 512 MiB RAM
    • Single-node configuration
    • EBS storage included
  • Postgres EBS HA (ARM64 PS-5)$15/month
    • 512 MiB RAM
    • 3-node high-availability setup
    • 1 primary + 2 replicas
  • Postgres Metal (M-10)$50/month
    • 1/8 vCPU, 1 GiB RAM
    • 3-node HA configuration
    • 10 GiB NVMe storage included
  • Vitess Non-Metal 3-Node$39/month
    • Sharding-capable database
    • x86-64 architecture
    • 3-node configuration

Which should you pick?

Choose Comet ML if

  • You need experiment tracking.
  • You want to start without paying.
  • You work on Web, Linux, Mac, Windows.
  • You also want code versioning.

Choose PlanetScale if

  • You need database branching.
  • You want to start without paying.
  • You work on Cloud-hosted (AWS, GCP, Azure).
  • You also want non-blocking schema changes.

Questions people ask

Is Comet ML or PlanetScale better?
Neither clearly leads. Comet ML starts at Free and PlanetScale at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Comet ML or PlanetScale?
Comet ML starts at Free and PlanetScale at Free.
Does Comet ML or PlanetScale run on more platforms?
Comet ML runs on Web, Linux, Mac, Windows. PlanetScale runs on Cloud-hosted (AWS, GCP, Azure).
Can I use Comet ML for free?
Both have a free tier, so you can try either at no cost before committing.
What is Comet ML best used for?
Comet ML is most often used for llm observability and monitoring, ai agent testing and debugging, experiment tracking for machine learning, model registry and version management. Of those, llm observability and monitoring and ai agent testing and debugging are not what PlanetScale is typically brought in for.
What can Comet ML do that PlanetScale cannot?
Comet ML covers Experiment tracking, Code versioning, Model registry, Hyperparameter optimization. PlanetScale covers Database Branching, Non-blocking Schema Changes, Insights, Horizontal Scaling. Both handle Web support.

Answered from the vendors’ own pages

Comet ML: Does Comet.ml offer a free plan?

Yes, Comet.ml offers free tiers for both Opik (cloud observability) and MLOps platforms. Free Cloud Opik includes up to 10 team members and 25,000 spans/month. Free MLOps tier is limited to 1 user.

Source
PlanetScale: How much does a PlanetScale Postgres database cost per month?

PlanetScale Postgres pricing starts at $5/month for single-node ARM64 configurations with 512 MiB RAM and $15/month for the same specs in high-availability mode with 1 primary and 2 replicas. Metal tier starts at $50/month for M-10 configuration (1/8 vCPU, 1 GiB RAM). Exact pricing depends on cluster size, node architecture (ARM64 vs x86-64), storage configuration, and selected AWS/GCP region.

Source
Comet ML: How many team members can use the free Comet.ml tier?

Free Cloud supports up to 10 team members. The Pro Cloud plan supports up to 50 team members at $19/month.

Source
PlanetScale: Is there a free tier for PlanetScale?

PlanetScale offers a free tier for development and testing workloads. After free tier limits are reached, usage-based pricing applies starting at $5/month for the smallest Postgres single-node configuration, with costs scaling based on cluster size, compute, storage, and additional features like dedicated PgBouncer or replicas.

Source
Comet ML: What is a span in Comet.ml pricing?

A span represents a single tracked operation such as model requests or function calls. Free Cloud tier includes 25,000 spans per month.

Source
PlanetScale: What is the difference between PlanetScale ARM64 and x86-64 pricing?

ARM64 instances cost significantly less than x86-64 equivalents. For example, a Postgres EBS HA cluster with 512 MiB RAM costs $15/month on ARM64 but $39/month on x86-64. This pricing difference extends across all cluster sizes, with larger x86-64 configurations reaching up to $5,599/month compared to ARM64 alternatives.

Source
Comet ML: Does Comet.ml offer academic pricing?

Yes, a free Pro plan is available for academic users; verification is required via signup.

Source
PlanetScale: What is included in a PlanetScale cluster price versus additional costs?

The advertised cluster price covers the base compute and configured storage. Additional charges apply for EBS storage beyond the base allocation, backup storage, data egress, optional dedicated PgBouncer connections, and replicas beyond the base high-availability configuration. Regional pricing varies across 17+ AWS and GCP zones.

Source
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