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92
Prague, Czech Republic Late Stage / Private

Intelligent Multi-Engine Database Environment

JetBrains s.r.o. • Led by Sergey Dmitriev, Valentin Kipiatkov, Eugene Belyaev

🔒 Confidential
COI SCORE 92 VERIFIED

🔬 The Innovation Core

The Pain Point

DBAs and backend engineers waste hours context-switching between fragmented, vendor-specific tools (e.g., pgAdmin for Postgres, SSMS for SQL Server), struggling with slow schema introspection on large data warehouses.

The Solution

A unified, intelligent IDE that supports 25+ database engines (PostgreSQL, AWS Redshift, Snowflake, Mongo, etc.) in a single interface. It differentiates via 'Intelligent Introspection'—indexing source code to provide refactoring and auto-completion for SQL just like Java/Python code.

⚡ Verified Impact

● Validated
30+ (SQL & NoSQL)Supported Engines
15.9M (Parent Ecosystem)User Base
40% Faster Query Writing (AI Assist)Efficiency
+60% via 'Level 1' ScanIntrospection Speed
CERTIFICATION

Gold Standard

TRL 9/9

📊 Market Traction

Revenue History ($M)

Market Share

🧠 Analyst Verdict: Industry Standard

"DataGrip has effectively commoditized the specialized database client market by offering a 'Super-IDE' that works across all major engines. While free tools like DBeaver dominate casual usage, DataGrip captures the high-value commercial segment by bundling with the JetBrains ecosystem, leveraging its deep semantic understanding of SQL code to justify the subscription cost."

✅ Pros

  • Unified Ecosystem: Single license covers Oracle, Postgres, Mongo, and Snowflake, eliminating the need for multiple vendor tools.
  • Semantic SQL Analysis: Treats SQL like code (refactoring, variable detection) rather than just text, reducing runtime errors.
  • Local Mode: 'Introspection by Levels' allows users to work with massive cloud schemas (e.g., BigQuery) without waiting for full metadata downloads.

⚠️ Risks

  • Resource Heavy: Java-based architecture consumes significantly more RAM/CPU than native clients like TablePlus.
  • Cold Start Time: Initial schema indexing for large enterprise databases can be slower than lightweight clients.
  • Cost Barrier: Subscription-only model pushes hobbyists toward free alternatives like DBeaver.

🛠️ Use Cases

💡
Cross-Cloud Analytics

Querying AWS Redshift and Snowflake in the same window without switching apps.

💡
Legacy Migration

Safely refactoring stored procedures (renaming variables) across thousands of lines of legacy PL/SQL.

💡
Data Ops

Visualizing query execution plans to optimize slow-running queries before deployment.

Market Maturity

Stop Guessing.
Know What's Deployable.

Marketing brochures look the same for TRL-3 (Concept) and TRL-9 (Proven) tech. Our radar cuts through the noise, showing you exactly if this innovation has crossed the "Pilot-to-Production" chasm.

9

Commercial Grade

Fully audited operational history. Ready for scale.

6

Prototype / Pilot

Functional in relevant environments. High risk, high reward.

Current Maturity Status

TRL Score 9.0 / 9.0
  • check_circle Technology validated in lab (TRL 4)
  • check_circle System prototype demonstration (TRL 7)
  • check_circle Actual system proven in operations (TRL 9)
Transparency

Forensic Evidence Chain

We don't just "approve" listings. We build a permanent, immutable audit trail for every verified claim. See exactly what was checked, when, and by whom.

View Sample Audit Report →

Technical Diligence

> Architecture Review: PASS
> Security Audit: ISO 27001
> Scalability Test: 10k TPS

Customer Verification

> Client Interview: #8821
> Deployment Status: LIVE
> ROI Confirmed: 18% Savings

Certification Issued

STATUS: VERIFIED verified

Enterprise Action Center

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🚀
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💡
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⭐
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🛡️
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