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The database industry is rapidly changing as companies build tools to support artificial intelligence.
For example, Innovaccer has raised over $654M to manage healthcare data. Meanwhile, newer companies like LangChain are creating tools for developers working with large language models.
Below is our list of 83 Database startups worth keeping an eye on.
Everything you need to raise funding for your startup, including 3,500+ investors, 7 tools, 18 templates and 3 learning resources.
Buy It For $97 $297 →Information about the industries, countries, and cities they generally invest in.
Get the Sheet for $50Information about their valuation, HQ's location, founded year, name of founders, funding amount and number of employees.
Get the Sheet for $50List of startup investors in the BioTech, Health, and Medicine industries, along with their Twitter, LinkedIn, and email addresses.
Get the Sheet for $50List of 250 startup investors in the AI and Machine Learning industries, along with their Twitter, LinkedIn, and email addresses.
Get the Sheet for $50List of 250 startup investors in the FinTech and Finance industries, along with their Twitter, LinkedIn, and email addresses.
Get the Sheet for $50VAST Data builds a unified data platform that integrates storage, database, and compute capabilities into a single software system. Their platform is engineered to simplify data infrastructure for demanding AI and deep learning workloads.
Neon builds a serverless PostgreSQL platform that separates storage and compute, enabling features like autoscaling and bottomless storage. The open-source database is known for its unique branching capabilities, which allow developers to instantly create copies of their data for development and testing.
LangChain develops an open-source framework that helps developers build applications using large language models. The platform provides the essential building blocks for chaining LLMs with other sources of computation or data, making it easier to create sophisticated AI products.
Innovaccer built a health cloud platform that uses AI to unify disparate patient data into a single, comprehensive record. Their technology enables healthcare organizations to apply advanced analytics, improving care management and overall patient outcomes.
Intella develops AI-powered tools for enterprises focused on Arabic speech, offering solutions for transcription and conversational analytics. Their platform enables companies to analyze these interactions and deploy AI agents for improved customer engagement.
Redis provides a real-time data platform centered on its popular open-source, in-memory database. The technology is widely used for high-performance applications like caching, session management, and real-time analytics that demand sub-millisecond speeds.
Starburst builds a data lakehouse platform that gives teams a single point of access to their data across cloud, on-premise, and hybrid environments. The platform is designed for running fast analytics directly on any data source, removing the need to move or copy data.
Pinecone develops a vector database that makes it easy to connect company data with generative AI models. Their technology allows developers to build applications that can provide highly relevant answers and recommendations by searching through large datasets.
Hydrolix developed a streaming data lake that combines real-time query performance with significant data compression. The platform allows companies to affordably store and analyze high-volume observability and security data.
Crunchbase operates a predictive intelligence platform that delivers live data and insights on private companies. Their comprehensive database on private companies, funding rounds, and market signals makes it a go-to tool for prospecting and industry research.
The top 10 are just a small part of a much wider story happening in the database world. The rest of the companies on our list have raised over $5 billion together, many of them building tools for analytics and AI.
Some are early in their journey, while others have been growing for years. Below are the other startups we think are worth watching.
| Startup | Main Industry | Year Founded | Amount Raised | Last Funding Round |
|---|---|---|---|---|
| Analytics | 2022 | $100M | Series B | |
| Data | 2021 | $26M | Series A | |
| Analytics | 2021 | $750M | Series C | |
| Security | 2020 | $233M | Series D | |
| Fintech | 2017 | $100M | Series B | |
| AI | 2017 | $115M | Series B | |
| Analytics | 2009 | $241M | Venture Round | |
| Analytics | 2017 | $113M | Series B | |
| Analytics | 2011 | $464.1M | Series F | |
| Infrastructure | 2017 | $54.4M | Seed | |
| Infrastructure | 2021 | $94M | Series B | |
| AI | 2020 | $496.1M | Series E | |
| Data | 2016 | $510M | Private Equity | |
| Fintech | 2023 | $43M | Series A | |
| Enterprise | 2018 | $25M | Series A | |
| Analytics | 2017 | $4.5M | Angel | |
| AI | 2018 | $45M | Series B | |
| Analytics | 2007 | $805.1M | Private Equity | |
| Analytics | 2016 | $100M | Private Equity | |
| Analytics | 2020 | $17.5M | Series A | |
| Marketing | 2015 | $30M | Series A | |
| AI | 2019 | $67.7M | Series B | |
| Analytics | 2010 | $26.6M | Venture Round | |
| Biotech | 2018 | $6.3M | Seed | |
| Infrastructure | 2018 | $105M | Series C | |
| AI | 2021 | $375k | Pre-Seed | |
| Analytics | 2019 | $82M | Series B | |
| Energy | 2014 | $575.5M | Series E | |
| Infrastructure | 2012 | $27M | Series C | |
| Cloud | 2024 | $2.1M | Pre-Seed | |
| AI | 2023 | ₩21B | Seed | |
| Mobility | 2016 | $111M | Venture Round | |
| Analytics | 2023 | $8.2M | Venture Round | |
| Analytics | 2018 | $80.3M | Series B | |
| AI | 2023 | $9M | Seed | |
| AI | 2022 | $30M | Series A | |
| AI | 2023 | $3M | Seed | |
| AI | 2022 | $20.5M | Series A | |
| Infrastructure | 2023 | $6.6M | Seed | |
| Infrastructure | 2015 | $80.1M | Series B | |
| Hardware | 2007 | $39.9M | Series C | |
| Infrastructure | 2020 | $59M | Series B | |
| Data | 2020 | $59.4M | Secondary Market | |
| Infrastructure | 2015 | CN¥130M | Series A | |
| AgTech | 2020 | €33.5M | Seed | |
| Cloud | 2010 | €120M | Debt Financing | |
| Analytics | 2016 | CN¥100M | Series B | |
| Media | 2022 | €1.4M | Seed | |
| AI | 2017 | €6M | Series A | |
| Infrastructure | 2022 | €20M | Series A | |
| Cloud | 2017 | €1.6M | Convertible Note | |
| Analytics | 2020 | $11M | Seed | |
| Infrastructure | 2017 | $4.7M | Pre-Seed | |
| Analytics | 2016 | $5M | Venture Round | |
| Enterprise | 2020 | $2.5M | Seed | |
| Infrastructure | 2019 | $3.5M | Seed | |
| Cloud | 2023 | $2.3M | Pre-Seed | |
| Infrastructure | 1995 | THB827.6M | Secondary Market | |
| Data | 2012 | $75M | Series D | |
| Analytics | 2016 | €3.2M | Seed | |
| Infrastructure | 2015 | €7.5M | Venture Round | |
| Infrastructure | 2000 | CN¥100M | Series A | |
| Analytics | 2014 | $2M | — | |
| Media | 2023 | €150k | Pre-Seed | |
| Cloud | 2021 | €400k | Seed | |
| Security | 2011 | €7.2M | Seed | |
| Analytics | 2022 | €400k | Pre-Seed | |
| Data | 2010 | — | — | |
| Infrastructure | 2021 | — | — | |
| Infrastructure | 1998 | — | — | |
| Infrastructure | 2005 | — | Seed | |
| Analytics | 2020 | — | — | |
| Infrastructure | 1986 | — | — |
