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Great for both ad-hoc analyzes and scheduled jobs
May 15, 2021

Great for both ad-hoc analyzes and scheduled jobs

Ender Ortak | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User

Overall Satisfaction with Databricks Lakehouse Platform (Unified Analytics Platform)

We use Databricks Lakehouse Platform to transform IoT data and build data models for BI tools. It is being used by engineering and IT teams. We use it with a data lake platform, read the raw data and transform it to a suitable format for analytics tools. We run daily/hourly jobs to create BI models and save the resulting models back to data lake or SQL tables.
  • Ready-2-use Spark environment with zero configuration required
  • Interactive analysis with notebook-style coding
  • Variety of language options (R, Scala, Python, SQL, Java)
  • Scheduled jobs
  • Random task failures
  • Hard to debug code
  • Hard to profile code
  • Scalable processing
  • Notebook-based codebase
  • Scheduled jobs
  • Supports end-customer dashboards
  • Provides a fast analysis platform
  • Supports BI dashboards for engineering teams

Do you think Databricks Lakehouse Platform delivers good value for the price?

Yes

Are you happy with Databricks Lakehouse Platform's feature set?

Yes

Did Databricks Lakehouse Platform live up to sales and marketing promises?

I wasn't involved with the selection/purchase process

Did implementation of Databricks Lakehouse Platform go as expected?

I wasn't involved with the implementation phase

Would you buy Databricks Lakehouse Platform again?

Yes

It is great for both ad-hoc analyzes and scheduled jobs. It supports most of the cloud storage technologies and provides an easy to use API to connect with them. Clusters can be auto scaled with the load, and you can also create temporary clusters for job runs, which cost less compared to all purpose clusters.