Softwr

Software · head to head

Databricks vs TensorBoard

Databricks logo

Databricks

Software

Unified analytics platform for data engineering and data science

From
Free
Rated
-
Full reviewWebsite
T

TensorBoard

Software

TensorFlow's visualization toolkit

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Databricks cloud compute is billed separately by the cloud provider on top of Databricks DBU charges; TensorBoard built and documented as a TensorFlow companion tool; the project's own site presents it as inspecting TensorFlow runs and graphs specifically, per tensorflow.org/tensorboard.

Where they differ

Only the attributes on which Databricks and TensorBoard actually diverge.

Attributes where Databricks and TensorBoard differ
AttributeDatabricksTensorBoard
Pricing modelusage-basedopen-source
PlatformsWeb, Aws, Azure, GcpWeb
Founded2013Unknown

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

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 TensorBoard
  • Building a lakehouse over data in cloud object storagenot TensorBoard
  • Training and serving machine learning models alongside the datanot TensorBoard

TensorBoard

No use cases recorded yet. See the TensorBoard review.

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

TensorBoard

  • Built and documented as a TensorFlow companion tool; the project's own site presents it as inspecting TensorFlow runs and graphs specifically, per tensorflow.org/tensorboard.
  • Source is Apache-2.0 licensed on GitHub (github.com/tensorflow/tensorboard), so there is no vendor-hosted paid tier or support contract distinct from the open source project.

Pricing, plan by plan

Databricks

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

TensorBoard

Free

No published plan breakdown. See the TensorBoard 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 TensorBoard if

  • You want to start without paying.
TensorBoard review

Questions people ask

Is Databricks or TensorBoard better?
Neither clearly leads. Databricks starts at Free and TensorBoard at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Databricks or TensorBoard?
Databricks starts at Free and TensorBoard at Free.
Does Databricks or TensorBoard run on more platforms?
Databricks runs on Web, Aws, Azure, Gcp. TensorBoard runs on Web.
Can I use Databricks for free?
Both have a free tier, so you can try either at no cost before committing.
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 TensorBoard is typically brought in for.
What can Databricks do that TensorBoard cannot?
Databricks covers Delta Lake, Apache Spark, MLflow, Unity Catalog.
ShareXLinkedInRedditWhatsAppEmail

Related pages

More on Databricks

More on TensorBoard

Keep looking

Other head to heads