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Databricks vs Groq

Databricks logo

Databricks

Software

Unified analytics platform for data engineering and data science

From
Free
Rated
-
Full reviewWebsite
Groq logo

Groq

Software

Fast inference provider using proprietary LPU hardware for low-latency serving

From
On request
Rated
-
Full reviewWebsite

The short version

  • Only Databricks has a free tier, so it costs nothing to try first.
  • Each has a real cost: Databricks cloud compute is billed separately by the cloud provider on top of Databricks DBU charges; Groq pricing is not published and is sold entirely by quote, making cost comparison difficult

Where they differ

Only the attributes on which Databricks and Groq actually diverge.

Attributes where Databricks and Groq differ
AttributeDatabricksGroq
Starting priceFreeOn request
Pricing modelusage-basedquote
Free tierYesNo
PlatformsWeb, Aws, Azure, GcpAPI, Cloud
Founded2013Unknown

Identical on both: 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 Databricks

  • Delta Lake
  • Apache Spark
  • MLflow
  • Unity Catalog
  • Photon Engine
  • Collaborative Notebooks
  • Auto-scaling
  • AWS

Only in Groq

Nothing recorded that Databricks does not also cover.

What people use each for

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

Databricks

  • Running Spark data engineering pipelines on managed clustersnot Groq
  • Building a lakehouse over data in cloud object storagenot Groq
  • Training and serving machine learning models alongside the datanot Groq

Groq

  • Latency-sensitive applications requiring sub-second inference response timesnot Databricks
  • High-volume inference workloads where cost per inference matters at scalenot Databricks
  • Custom model deployment with performance guaranteesnot Databricks
  • Enterprise applications seeking inference-specific infrastructurenot Databricks

Where each one falls short

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

Databricks

  • Cloud compute is billed separately by the cloud provider on top of Databricks DBU charges
  • The free trial lasts 14 days
  • Discounts require a Committed Use Contract, with larger commitments needed for larger discounts
  • Azure Databricks pricing is set by Microsoft rather than by Databricks
  • Security and compliance capabilities are sold as separate platform add ons rather than included in the base rate

Groq

  • Pricing is not published and is sold entirely by quote, making cost comparison difficult
  • Limited to open-weight models; no proprietary model access through the platform
  • Not widely integrated into third-party AI platforms compared to OpenAI or Anthropic

Pricing, plan by plan

Databricks

Free
  • Community EditionFree
    • Limited cluster
    • Notebook environment
    • Community support
  • Standard$0.07/DBU
    • Jobs compute
    • SQL compute
    • Standard support

Groq

On request

No published plan breakdown. See the Groq review.

Which should you pick?

Choose Databricks if

  • You need delta lake.
  • You want to start without paying.
  • You work on Web, Aws, Azure, Gcp.
  • You also want apache spark.
Databricks review

Choose Groq if

  • You work on API, Cloud.
Groq review

Questions people ask

Is Databricks or Groq better?
Neither clearly leads. Databricks starts at Free and Groq at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Databricks or Groq?
Databricks has a free tier; the other does not. Paid plans start at Free for Databricks and On request for Groq.
Does Databricks or Groq run on more platforms?
Databricks runs on Web, Aws, Azure, Gcp. Groq runs on API, Cloud.
Can I use Databricks for free?
Yes. Databricks has a free tier, so you can try it without paying. Groq starts at On request.
What is Databricks best used for?
Databricks is most often used for running spark data engineering pipelines on managed clusters, building a lakehouse over data in cloud object storage, training and serving machine learning models alongside the data. Of those, running spark data engineering pipelines on managed clusters and building a lakehouse over data in cloud object storage are not what Groq is typically brought in for.
What can Databricks do that Groq cannot?
Databricks covers Delta Lake, Apache Spark, MLflow, Unity Catalog.
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