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FOUNDERS[PRIME]
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Open - Rolling BasisSaaS DiscountslockPro

Databricks for Startups — $50,000 in Platform Credits

domainDatabricksverifiedVerified · Last checked Jan 27
Deal Value
$50,000 in platform credits
timerTime~15 min
task_altApproval1-7 days
eventDeadlineRolling
timer
Time
~15 min
task_alt
Approval
1-7 days
speed
Difficulty
Medium
trending_up
Success
75%+

infoAbout This Deal

Databricks for Startups provides up to $50,000 in platform credits to VC-funded startups building data-driven applications on the Databricks Lakehouse Platform. The program offers enterprise-grade unified data analytics, AI/ML capabilities, and expert technical support to help startups scale from MVP to IPO.

inventory_2What's Included

4 items
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Value

$50,000 in platform credits

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Provider

Databricks

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Category

SaaS Discounts

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Savings

Save $50,000

checklistEligibility

6 items
  • arrow_rightVC-funded startup (raised institutional funding)
  • arrow_rightBuilding data-driven applications (core to business model)
  • arrow_rightData analytics or AI/ML focus (using data at scale)
  • arrow_rightActive product development (not just research or POC)
  • arrow_rightScalable data infrastructure needs (processing large datasets)

directions_runHow to Apply

11 steps
  1. 1
    Step 1.Visit the Databricks for Startups application portal
  2. 2
    Step 2.Complete the online application form with company information and founding details
  3. 3
    Step 3.Provide VC funding information (investors, round, amount)
  4. 4
    Step 4.Describe your product and data/AI use case
  5. 5
    Step 5.Specify expected Databricks usage and technical requirements
  6. 6
    Step 6.Include current stage and growth metrics
  7. 7
    Step 7.Submit pitch deck (optional but recommended)
  8. 8
    Step 8.Await review (7-14 day evaluation period)
  9. 9
    Step 9.Receive approval decision via email
  10. 10
    Step 10.Set up Databricks account with approved credits
  11. 11
    Step 11.Onboard with technical team to optimize platform usage

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tagTags & Categories

#data-analytics#ai#ml#lakehouse#cloud-credits#big-data#startups#databricks