Anonymous UserLead Data Architect at a government
We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
"Whenever we want to find the actual costing, we have to send an email to Databricks, so having the information available on the internet would be helpful."
"I do not exactly know the costs, but one of our clients pays between $100 USD and $200 USD monthly."
"Licensing on site I would counsel against, as on-site hardware issues tend to really delay and slow down delivery."
"We find Databricks to be very expensive, although this improved when we found out how to shut it down at night."
"The pricing depends on the usage itself."
"I am based in South Africa, where it is expensive adapting to the cloud, and then there is the price for the tool itself."
"The price is okay. It's competitive."
"Databricks uses a price-per-use model, where you can use as much compute as you need."
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Databricks creates a Unified Analytics Platform that accelerates innovation by unifying data science, engineering, and business. It utilizes Apache Spark to help clients with cloud-based big data processing. It puts Spark on “autopilot” to significantly reduce operational complexity and management cost. The Databricks I/O module (DBIO) improves the read and write performance of Apache Spark in the cloud. An increase in productivity is ensured through Databricks’ collaborative workplace.
Databricks is ranked 2nd in Data Science Platforms with 21 reviews while Teradata Data Lab is ranked 28th in Business Intelligence (BI) Tools. Databricks is rated 8.0, while Teradata Data Lab is rated 0.0. The top reviewer of Databricks writes "Has a good feature set but it needs samples and templates to help invite users to see results". On the other hand, Databricks is most compared with Amazon SageMaker, Microsoft Azure Machine Learning Studio, Azure Stream Analytics, Alteryx and Dataiku Data Science Studio, whereas Teradata Data Lab is most compared with Tableau, Microsoft BI, MicroStrategy and Anaconda.
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