20 data infrastructure investors subsidizing databases and dev tools in 2025

Most VCs claim they invest in infrastructure, but few actually understand database internals or why developers choose one data platform over another. You need investors who've backed companies through the long enterprise adoption cycles and won't panic when your sales motion takes 9 months because engineers need to evaluate your product thoroughly.

Quick list

Finding investors who understand data infrastructure

Experience: Find investors who've backed database companies through their first 100 enterprise customers. Most don't understand why developers need 6 months to evaluate your database or why you can't just "move faster" with mission-critical data infrastructure. See how others handle this in our guide to effective outreach.

Network: Check if they can introduce you to platform teams at Fortune 500 companies or CTOs at high-growth startups. Those relationships matter more than generic developer connections, especially when you need to send pitch decks that highlight deep technical capabilities.

Alignment: Seed investors often don't understand why your ARR grows slowly when you're building bottom-up with developers who take time to evaluate. Consumer tech investors won't get why usage-based pricing means lumpy revenue.

Track record: Look at whether their portfolio companies reached meaningful scale or stayed stuck at small dev-tool revenue. Lots of GitHub stars without revenue is a red flag—especially if you're not using proper PDF controls to manage what you send out.

Communication: Use Ellty to share your deck with trackable links. You'll see who actually opens your technical architecture slides and performance benchmarks—similar to the way strong DocSend alternatives provide visibility.

Value-add: Ask what technical background their partners have. Generic "we invest in SaaS" investors can't help you think through distributed systems tradeoffs or CAP theorem decisions.

Reaching data infrastructure investors

Identify potential investors: Research recent database and dev tool deals on Pitchbook. Application-layer VCs won't lead your infrastructure round even if they claim to do developer tools.

Craft a compelling pitch: Show your query performance benchmarks, developer adoption metrics, and technical differentiation. Most investors are tired of "Postgres but faster" claims without actual TPC-H results or customer migration stories.

Share your pitch deck: Upload to Ellty and send trackable links. Monitor which pages investors spend time on—if they skip your architecture diagrams, they probably don't have technical partners.

Utilize your network: Message portfolio CTOs on LinkedIn and ask about investor technical depth and actual help with hiring infrastructure engineers. Most will tell you if the VC understands databases or just pattern-matches to Snowflake.

Attend networking events: Data Council and QCon are where infrastructure deals happen. Skip generic SaaS conferences where nobody understands ACID guarantees.

Engage on online platforms: Connect with partners on LinkedIn after a portfolio CTO intro. Cold outreach to infrastructure investors works better than with consumer VCs if you have strong GitHub traction. For sensitive architecture materials, consider DPA-compliant sharing.

Organize due diligence: Set up an Ellty data room with your benchmark results, architecture docs, and design partner agreements before they ask. It speeds up the process.

Set up introductory meetings: Lead with your technical differentiation and developer traction metrics. Don't waste time on TAM slides about the database market—they know it's huge.

Why data infrastructure funding matters now

Data infrastructure investment hit $15B in 2024 according to PitchBook, with focus shifting to specialized databases and AI infrastructure. The AI boom drove demand for vector databases and real-time data platforms. Companies raised $50B+ for AI applications in 2024, creating massive derivative demand for underlying data infrastructure. VCs deployed $3B+ into database and data platform startups, focusing on products with strong developer adoption and clear paths to enterprise revenue. If you're raising in Q1 2025, investors want to see weekly active developers and early enterprise design partners, not just open source stars.

20 top data infrastructure investors

1. Accel

Sand Hill Road firm that backed Pinecone and understands why vector databases matter for AI applications.

• Recent Deals: Pinecone $100M Series B (Sep 2025), Astronomer $213M Series C (Jun 2024), Snorkel AI $135M Series C (Apr 2024)
• LinkedIn: Arun Mathew LinkedIn
• Sector Focus: vector databases, data observability, workflow orchestration, ML infrastructure, analytics platforms
• Stage Focus: Series A, Series B, Series C
• Location: Palo Alto, USA
• Website: accel.com

2. Andreessen Horowitz

a16z's infrastructure team writes massive checks for proven data platforms with enterprise traction like Databricks.

• Recent Deals: Databricks $500M Series I (Aug 2025), Weights & Biases $200M Series D (Jun 2024), dbt Labs $222M Series D (Feb 2024)
• LinkedIn: Martin Casado LinkedIn
• Sector Focus: data warehouses, ML platforms, analytics infrastructure, data governance, ETL platforms
• Stage Focus: Series B, Series C, Growth
• Location: Menlo Park, USA
• Website: a16z.com

3. Greylock Partners

Partnership that backed Couchbase and multiple database companies through long enterprise sales cycles.

• Recent Deals: Couchbase $105M Series G (Jul 2025), Arize AI $38M Series B (May 2024), Chronosphere $115M Series C (Mar 2024)
• LinkedIn: Jerry Chen LinkedIn
• Sector Focus: NoSQL databases, observability platforms, ML monitoring, distributed systems, data platforms
• Stage Focus: Series A, Series B, Series C
• Location: Menlo Park, USA
• Website: greylock.com

4. Index Ventures

European fund with strong technical team that understands vector search and modern database architecture.

• Recent Deals: Weaviate $50M Series B (Jun 2025), Databricks $1.6B Series H (Aug 2023), Confluent IPO (Sep 2021)
• LinkedIn: Mike Volpi LinkedIn
• Sector Focus: vector databases, streaming platforms, distributed databases, search infrastructure, data platforms
• Stage Focus: Series B, Series C, Growth
• Location: London, UK
• Website: indexventures.com

5. Amplify Partners

Infrastructure specialist fund that only backs technical founders building hard infrastructure problems.

• Recent Deals: Materialize $60M Series C (May 2025), Keygen $18M Series A (Mar 2024), Metaplane $8.4M Series A (Jan 2024)
• LinkedIn: Lenny Pruss LinkedIn
• Sector Focus: streaming databases, data observability, developer infrastructure, database internals, real-time analytics
• Stage Focus: Seed, Series A, Series B
• Location: Menlo Park, USA
• Website: amplifypartners.com

6. Battery Ventures

Growth equity firm that backed ClickHouse's massive round and understands OLAP database economics.

• Recent Deals: ClickHouse $250M Series C (Apr 2025), Kong $175M Series E (Mar 2024), Starburst $250M Series D (May 2024)
• LinkedIn: Neeraj Agrawal LinkedIn
• Sector Focus: OLAP databases, API infrastructure, data warehouses, analytics platforms, database management
• Stage Focus: Series C, Series D, Growth
• Location: Boston, USA
• Website: battery.com

7. Benchmark

Iconic firm that backs technical founders building developer-first products like Convex.

• Recent Deals: Convex $26M Series A (Mar 2025), Crunchy Data $105M Series A (Jan 2024), Confluent IPO (Sep 2021)
• LinkedIn: Peter Fenton LinkedIn
• Sector Focus: reactive backends, managed Postgres, streaming platforms, developer infrastructure, database hosting
• Stage Focus: Series A, Series B
• Location: Menlo Park, USA
• Website: benchmark.com

8. Bessemer Venture Partners

Multi-stage fund with dedicated cloud practice that backed Fivetran through massive data pipeline growth.

• Recent Deals: Fivetran $565M Series D (Feb 2025), Canva $200M Series F (Sep 2024), HashiCorp IPO (Dec 2021)
• LinkedIn: Janelle Teng LinkedIn
• Sector Focus: data pipelines, ETL platforms, data integration, workflow automation, infrastructure software
• Stage Focus: Series B, Series C, Growth
• Location: Menlo Park, USA
• Website: bvp.com

9. GV (Google Ventures)

Corporate VC from Google that backed Cockroach Labs and understands distributed systems at scale.

• Recent Deals: Cockroach Labs $278M Series F (Jan 2025), Cribl $150M Series D (Oct 2023), Timescale $110M Series C (Aug 2024)
• LinkedIn: Karim Faris LinkedIn
• Sector Focus: distributed SQL, log management, time-series databases, cloud-native databases, observability
• Stage Focus: Series B, Series C, Growth
• Location: Mountain View, USA
• Website: gv.com

10. First Round Capital

Early-stage firm that backed DuckDB Labs and understands bottom-up developer adoption.

• Recent Deals: DuckDB Labs $40M Series A (Dec 2024), Incident.io $35M Series B (Jul 2024), Square IPO (Nov 2015)
• LinkedIn: Josh Kopelman LinkedIn
• Sector Focus: embedded databases, analytics engines, developer tools, incident management, infrastructure software
• Stage Focus: Seed, Series A
• Location: Philadelphia, USA
• Website: firstround.com

11. Lightspeed Venture Partners

Multi-stage fund that backed PlanetScale and understands serverless database economics.

• Recent Deals: PlanetScale $50M Series C (Nov 2024), Chronosphere $115M Series C (Mar 2024), Affirm IPO (Jan 2021)
• LinkedIn: Gaurav Gupta LinkedIn
• Sector Focus: serverless databases, MySQL at scale, observability platforms, data infrastructure, cloud databases
• Stage Focus: Series A, Series B, Series C
• Location: Menlo Park, USA
• Website: lsvp.com

12. Madrona Venture Group

Seattle-based fund that backs infrastructure companies and understands log management and observability.

• Recent Deals: Seq $30M Series B (Oct 2024), Hightouch $54M Series B (May 2023), Snowflake IPO (Sep 2020)
• LinkedIn: Tim Porter LinkedIn
• Sector Focus: log management, observability, data platforms, analytics infrastructure, cloud infrastructure
• Stage Focus: Series A, Series B
• Location: Seattle, USA
• Website: madrona.com

13. NEA

Large fund with infrastructure practice that backed SingleStore through multiple rounds and understands distributed databases.

• Recent Deals: SingleStore $116M Series F (Sep 2024), Databricks $1.6B Series H (Aug 2023), MongoDB IPO (Oct 2017)
• LinkedIn: Tony Florence LinkedIn
• Sector Focus: distributed databases, real-time analytics, in-memory databases, data platforms, cloud infrastructure
• Stage Focus: Series C, Series D, Growth
• Location: Menlo Park, USA
• Website: nea.com

14. Redpoint Ventures

Infrastructure-focused firm that backed Timescale and understands time-series database use cases.

• Recent Deals: Timescale $110M Series C (Aug 2024), Cribl $150M Series D (Oct 2023), Snowflake IPO (Sep 2020)
• LinkedIn: Satish Dharmaraj LinkedIn
• Sector Focus: time-series databases, log analytics, observability, IoT data platforms, PostgreSQL extensions
• Stage Focus: Series B, Series C, Growth
• Location: Menlo Park, USA
• Website: redpoint.com

15. Sequoia Capital

Top-tier firm that backed Neon and multiple database unicorns including MongoDB and Snowflake.

• Recent Deals: Neon $70M Series B (Jul 2024), Wiz $300M Series D (May 2024), Snowflake IPO (Sep 2020)
• LinkedIn: Roelof Botha LinkedIn
• Sector Focus: serverless Postgres, cloud databases, data warehouses, analytics platforms, infrastructure software
• Stage Focus: Series A, Series B, Series C, Growth
• Location: Menlo Park, USA
• Website: sequoiacap.com

16. Tiger Global

Growth fund that backs late-stage data companies with proven revenue and enterprise traction.

• Recent Deals: Airbyte $150M Series B (Jun 2024), Databricks $1.6B Series H (Aug 2023), Snowflake IPO (Sep 2020)
• LinkedIn: John Curtius LinkedIn
• Sector Focus: data integration, ETL platforms, data warehouses, analytics infrastructure, enterprise data platforms
• Stage Focus: Series C, Growth
• Location: New York, USA
• Website: tigerglobal.com

17. Kleiner Perkins

Historic firm with infrastructure practice that backed Starburst and understands query engine economics.

• Recent Deals: Starburst $250M Series D (May 2024), WorkOS $80M Series B (Mar 2024), Confluent IPO (Sep 2021)
• LinkedIn: Bucky Moore LinkedIn
• Sector Focus: query engines, data federation, distributed SQL, analytics platforms, database infrastructure
• Stage Focus: Series B, Series C, Growth
• Location: Menlo Park, USA
• Website: kleinerperkins.com

18. GGV Capital

Cross-border fund that backed Zilliz and understands open source database commercialization.

• Recent Deals: Zilliz $60M Series B (Apr 2024), PingCAP $270M Series D (Nov 2020), Databricks $1B Series G (Feb 2021)
• LinkedIn: Hans Tung LinkedIn
• Sector Focus: vector databases, distributed databases, open source databases, NewSQL, cloud-native databases
• Stage Focus: Series A, Series B, Series C
• Location: Menlo Park, USA
• Website: ggvc.com

19. CRV

Charles River Ventures backs developer tools like Steampipe and understands API-first infrastructure.

• Recent Deals: Steampipe $12M Series A (Mar 2024), Aiven $210M Series D (Nov 2021), PlanetScale $30M Series B (Jun 2021)
• LinkedIn: Reid Christian LinkedIn
• Sector Focus: cloud API querying, managed databases, developer infrastructure, data integration, SQL interfaces
• Stage Focus: Series A, Series B
• Location: Menlo Park, USA
• Website: crv.com

20. IA Ventures

Data-focused early-stage fund that backed Motherduck and only invests in companies building on proprietary data.

• Recent Deals: Motherduck $47.5M Series B (Feb 2024), Sigma Computing $200M Series D (May 2023), DataRobot $270M Series G (Jul 2021)
• LinkedIn: Roger Ehrenberg LinkedIn
• Sector Focus: cloud analytics, embedded analytics, data science platforms, analytics infrastructure, BI tools
• Stage Focus: Seed, Series A, Series B
• Location: New York, USA
• Website: iaventures.com

Track which investors engage with your technical content

These 20 investors closed deals from 2023 to November 2025. Before you start reaching out, set up proper tracking.

Upload your deck to Ellty and create a unique link for each investor. You'll see exactly which slides they view and how long they spend on your architecture diagrams or performance benchmarks. Most infrastructure founders are surprised to learn investors skip market size slides but spend 15+ minutes reviewing technical differentiation and query performance comparisons.

When investors ask for benchmark results or design partner feedback, share an Ellty data room instead of messy email threads. Your TPC-H results, architecture documentation, and early customer testimonials in one secure place with view analytics. You'll know if they're actually reviewing your technical details or just pattern-matching to Snowflake.

Common questions

How do I know if an investor understands databases?

Ask them about CAP theorem tradeoffs or why developers choose Postgres over MySQL. If they can't discuss technical architecture or reference portfolio companies' database decisions, they're not infrastructure investors.

Should I pitch application-layer VCs for database companies?

Only if they have multiple infrastructure investments. Application VCs won't understand why your GTM takes 18 months or why you need developers to evaluate for 6 months before purchasing.

What metrics do data infrastructure investors care about most?

Weekly active developers, time to first query, and enterprise design partners. GitHub stars matter less than actual production usage. Show how many companies run mission-critical workloads on your database.

How many investors should I contact for a data infrastructure raise?

Plan for 30-50 conversations to close a round. Infrastructure deals take 3-6 months because technical diligence is thorough. Start earlier than you think and keep multiple technical investors engaged.

When should I set up a data room?

Before sending your first deck. Infrastructure investors will ask for benchmark results, architecture docs, and customer references immediately. Having an Ellty data room ready speeds up diligence by 2-4 weeks.

Do infrastructure investors care about deck analytics?

Yes, especially if you're building analytics infrastructure. If you can't track which investors engage with your deck, it raises questions about your data competency. It shows you understand metrics and product instrumentation.