Databricks
Large (~7,000)
LangChain
Small (~230)
Best For
Databricks
Best for: Data engineers who want strong comp and deep technical pedigree at scale
LangChain
Best for: AI engineers who want to shape the open-source LLM tooling ecosystem from inside a fast-moving startup
Ratings
DatabricksLangChain
4.1
4.6
Overall
3.9
4.0
Work-Life Balance
4.0
4.7
Culture & Values
4.3
4.6
Comp & Benefits
3.8
4.4
Senior Mgmt
3.9
4.4
Career Opps
👍 82% Recommend
👤 88% CEO Approval (Ali Ghodsi)
👍 92% Recommend
👤 95% CEO Approval (Harrison Chase)
Culture Values
Databricks only
🌱 Learning & Growth💎 Strong Comp & Equity🌈 Diverse & Inclusive
LangChain only
🔓 Open Source🚀 Ship Fast & Iterate🌐 Remote-Friendly🧩 Wears Many Hats🤝 Flat Hierarchy
Shared
⚙️ Engineering-Driven🎯 Direct Product Impact
Pros & Cons
Databricks
- Engineers who built Spark, Delta Lake, MLflow — deep technical pedigree
- Strong compensation and equity packages consistently above market
- Hypergrowth means org changes are constant — teams restructure frequently
- Some legacy Spark-era tech debt that can slow down new features
LangChain
- Open-source DNA with massive community — your work impacts millions of developers
- Small team with outsized impact — ship fast with high autonomy
- Very early-stage startup — limited structure and processes
- Rapidly scaling which brings growing pains and role ambiguity
Bottom Line
Databricks
Choose Databricks if you want elite data infrastructure work with strong equity — but brace for constant org changes.
LangChain
Open-source DNA with massive developer community impact and high autonomy — but very early-stage with limited structure and rapidly shifting priorities.
Open Roles
Databricks — 842 jobs
💼 Sales / GTM
353
💻 Engineering
284
📋 Product
39
📣 Marketing
34
📊 Data
22
👤 HR / People
12
🧠 ML / AI
12
⚙️ Operations
11
🎨 Design
6
💰 Finance
5
⚖️ Legal
5
LangChain — 88 jobs
💻 Engineering
44
💼 Sales / GTM
29
📣 Marketing
7
👤 HR / People
3
🧠 ML / AI
1
⚙️ Operations
1
📋 Product
1
Summary
Databricks scores 4.1/5.0 on Glassdoor with a 3.9 work-life balance rating. LangChain scores 4.6/5.0 overall with a 4.0 WLB. That’s a 0.5-point gap on overall satisfaction.
Both companies share these culture values: Engineering-Driven, Direct Product Impact. Databricks also emphasizes Learning & Growth, Strong Comp & Equity, Diverse & Inclusive. LangChain also emphasizes Open Source, Ship Fast & Iterate, Remote-Friendly, Wears Many Hats, Flat Hierarchy.
On the hiring front, Databricks has 842 open roles and LangChain has 88 open roles.