C

Cockroach Labs

Distributed SQL database for cloud apps

Overview

Cockroach Labs builds and sells CockroachDB, a distributed SQL database designed for cloud applications. It runs across many servers and regions so it can store data locally where customers operate and still act as one global database. The product automatically distributes data and workload, scales elastically as demand grows, and keeps data consistent even if parts of the system fail, with options for cloud-based or on‑premises deployment. Revenue comes from subscription-based pricing based on usage and deployment choices. Compared with other databases, its key differences are multi-region, globally available data with regional sovereignty, continuous availability during failures, and strong SQL support used across environments. The company’s goal is to provide a scalable, reliable, and globally accessible database that helps modern cloud applications run smoothly in any region.

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About Cockroach Labs

Simplify's Rating
Why Cockroach Labs is rated
B-
Rated B on Competitive Edge
Rated B on Growth Potential
Rated C on Differentiation

Industries

Data & AnalyticsEnterprise Software

Company Size

501-1,000

Company Stage

Series F

Total Funding

$633.2M

Headquarters

New York City, New York

Founded

2015

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Simplify's Take

What believers are saying

  • Cockroach Continuum launched September 15, 2026 with consumption pricing and agentic operations.
  • BYOC reached general availability on September 24, 2026, widening cloud-account adoption.
  • IBM partnership deepens distribution through Power, Cloud, LinuxONE, Z, and OpenShift channels.

What critics are saying

  • Yugabyte's AWS collaboration and Meko target the same agentic database buyers in 2026.
  • Continuum's economics depend on adoption; weak conversion leaves costly shared capacity underutilized.
  • No recent public fundraising or acquisition signals suggest Cockroach Labs must win on revenue alone.

What makes Cockroach Labs unique

  • Cockroach Continuum on September 15, 2026 turns databases into one elastic estate.
  • IBM Power and LinuxONE support expands CockroachDB across entrenched enterprise infrastructure.
  • CockroachDB still promises zero-RPO global consistency across regions and failure domains.

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Funding

Total Funding

$633.2M

Above

Industry Average

Funded Over

7 Rounds

Series F funding comparison data is currently unavailable. We're working to provide this information soon!
Series F Funding Comparison Coming Soon

Benefits

  • Health Insurance
  • Paid Parental Leave
  • Flexible Work Hours
  • Unlimited Paid Time Off
  • Relocation Assistance
  • Professional Development Budget

Growth & Insights and Company News

Headcount

6 month growth

1%

1 year growth

2%

2 year growth

3%
VARINDIA
Sep 22nd, 2026
Matters.AI and Cockroach Labs Launch In-Environment Data Security for Distributed SQL, Mapping DPDP-Regulated Data to Every Database Role that can reach it.

Matters.AI and Cockroach Labs Launch In-Environment Data Security for Distributed SQL, Mapping DPDP-Regulated Data to Every Database Role that can reach it. Matters.AI and Cockroach Labs Launch In-Environment Data Security for Distributed SQL, Mapping DPDP-Regulated Data to Every Database Role Integration classifies CockroachDB data at the column level with 38 PII detectors, correlates it with users, roles and privilege grants, and flags over-privileged access and cross-border residency conflicts, without a single record leaving the customer's infrastructure Matters.AI, the Bengaluru-headquartered AI-native data security company, and Cockroach Labs, the New York-based maker of the distributed SQL database CockroachDB, today announced an integration that classifies personal and regulated data inside CockroachDB deployments at the column level and maps it to the exact database users, roles and privileges able to access it. The integration is available now to CockroachDB customers. The launch lands as Indian enterprises prepare for the Digital Personal Data Protection (DPDP) Rules, notified in November 2025, with the substantive obligations on data fiduciaries taking effect from May 2027. Banks, payment companies and insurers already operate under Reserve Bank of India data-localisation and cybersecurity mandates. Enterprises adopt distributed SQL precisely because it replicates data across regions for resilience, and that is exactly what makes the two questions every regulator now asks, "where is personal data, and who can reach it?", harder to answer, not easier. The integration scans CockroachDB databases, tables and columns with 38 personally identifiable information (PII) detectors covering eight regulatory jurisdictions, plus detection for payment card numbers, protected health information (PHI) and secrets stored in free-text columns. It then correlates every classified column with CockroachDB's users, roles and privilege grants to produce a live access map: which accounts can reach regulated data, which roles hold more privilege than they use, and where data sits in a jurisdiction it should not. Findings map directly to India's Digital Personal Data Protection Act, PCI DSS, HIPAA, GDPR, ISO 27001 and SOC 2. Classification and privilege analysis execute entirely inside the customer's own infrastructure, under the customer's IAM controls. Raw records and sampled values are never transmitted. Only findings and operational metadata reach the Matters.AI control plane. For regulated Indian entities that must keep customer data within the country, that architecture is not a preference. It is the requirement. "Enterprises distributed their databases to survive anything. In doing so, they made their most sensitive data harder to see than ever: more regions, more tables, more roles, and still no answer to the simplest question a CISO can ask: who can reach this data right now? With Cockroach Labs, Comprompt Solutions LLP is answering that at the column level, inside the customer's own environment. That's what an AI security engineer is for," said Keshava Murthy, co-founder and CEO of Matters.AI. The cost of not knowing is now on record. IBM's 2026 Cost of a Data Breach Report puts the average breach in India at a record ₹25.5 crore, up 15.9 per cent in a year, with financial services the most expensive sector at ₹40.9 crore per breach. Indian organisations without security automation took an average of 236 days to identify a breach. Under the DPDP Act, the Data Protection Board of India can impose penalties of up to ₹250 crore per instance for failing to implement reasonable security safeguards. "Together with Matters.AI, we're making data protection seamless for our customers. This integration gives teams instant visibility into where their sensitive data lives, who can access it, and what's happening to it, supporting their growth every step of the way," said Tejas Baldev, Vice President of Sales, APAC, Cockroach Labs. Cockroach Labs has operated an engineering centre in Bengaluru since 2023 and hosted its RoachFest customer conference in the city in 2025. Matters.AI raised US$6.25 million (about ₹55 crore) in seed and pre-seed funding in October 2025, co-led by Kalaari Capital and Endiya Partners, to build what it calls the first AI security engineer for enterprise data.

CxOToday
Sep 22nd, 2026
Matters.AI & Cockroach Labs Partner to Resolve "Distributed Data Blindspots" in Cloud SQL

Home media coverage Matters.AI & Cockroach Labs partner to resolve "distributed data blindspots" in cloud SQL. Sep. 22, 2026 at 4:22 pm Integration classifies CockroachDB data at the column level with 38 PII detectors, correlates it with users, roles and privilege grants, and flags over-privileged access and cross-border residency conflicts, without a single record leaving the customer's infrastructure. Matters.AI and Cockroach Labs today announced an integration that classifies personal and regulated data inside CockroachDB deployments at the column level and maps it to the exact database users, roles and privileges able to access it. The integration is available now to CockroachDB customers. The launch lands as Indian enterprises prepare for the Digital Personal Data Protection (DPDP) Rules, notified in November 2025, with the substantive obligations on data fiduciaries taking effect from May 2027. Banks, payment companies and insurers already operate under Reserve Bank of India data-localisation and cybersecurity mandates. Enterprises adopt distributed SQL precisely because it replicates data across regions for resilience, and that is exactly what makes the two questions every regulator now asks, "where is personal data, and who can reach it?", harder to answer, not easier. The integration scans CockroachDB databases, tables and columns with 38 personally identifiable information (PII) detectors covering eight regulatory jurisdictions, plus detection for payment card numbers, protected health information (PHI) and secrets stored in free-text columns. It then correlates every classified column with CockroachDB's users, roles and privilege grants to produce a live access map: which accounts can reach regulated data, which roles hold more privilege than they use, and where data sits in a jurisdiction it should not. Findings map directly to India's Digital Personal Data Protection Act, PCI DSS, HIPAA, GDPR, ISO 27001 and SOC 2. Classification and privilege analysis execute entirely inside the customer's own infrastructure, under the customer's IAM controls. Raw records and sampled values are never transmitted. Only findings and operational metadata reach the Matters.AI control plane. For regulated Indian entities that must keep customer data within the country, that architecture is not a preference. It is the requirement. "Enterprises distributed their databases to survive anything. In doing so, they made their most sensitive data harder to see than ever: more regions, more tables, more roles, and still no answer to the simplest question a CISO can ask: who can reach this data right now? With Cockroach Labs, we're answering that at the column level, inside the customer's own environment. That's what an AI security engineer is for," said Keshava Murthy, co-founder and CEO of Matters.AI. The cost of not knowing is now on record. IBM's 2026 Cost of a Data Breach Report puts the average breach in India at a record ₹25.5 crore, up 15.9 per cent in a year, with financial services the most expensive sector at ₹40.9 crore per breach. Indian organisations without security automation took an average of 236 days to identify a breach. Under the DPDP Act, the Data Protection Board of India can impose penalties of up to ₹250 crore per instance for failing to implement reasonable security safeguards. "Together with Matters.AI, we're making data protection seamless for our customers. This integration gives teams instant visibility into where their sensitive data lives, who can access it, and what's happening to it, supporting their growth every step of the way," said Tejas Baldev, Vice President of Sales, APAC, Cockroach Labs. Cockroach Labs has operated an engineering centre in Bengaluru since 2023 and hosted its RoachFest customer conference in the city in 2025. Matters.AI raised US$6.25 million (about ₹55 crore) in seed and pre-seed funding in October 2025, co-led by Kalaari Capital and Endiya Partners, to build what it calls the first AI security engineer for enterprise data.

PR Newswire
Sep 15th, 2026
Cockroach Labs launches Continuum, agentic database cloud pooling capacity across entire database estates

Cockroach Labs has launched Cockroach Continuum, a database cloud platform that enables enterprises to operate their entire database estate as a single elastic system. The platform pools capacity across databases, automates operations, and uses consumption-based pricing instead of charging for provisioned peak capacity. Continuum addresses the challenge of rapidly multiplying AI agents, which Gartner predicts could reach 150,000 per Fortune 500 company by 2028. The system runs on CockroachDB and includes database virtualisation, elastic storage, AI-assisted operations, and auto-scaling compute capabilities. Chief executive Spencer Kimball said the platform allows customers to scale without sacrificing resilience whilst putting idle capacity to work. The company, which serves clients including OpenAI, CoreWeave, and DoorDash, also unveiled a new brand identity reflecting its focus on the agentic era.

HN Notify
Sep 12th, 2026
MongoDB's growth prospects under scrutiny.

MongoDB's growth prospects under scrutiny. Sep 12, 2026 · dev MongoDB's Atlas dilemma: sustaining growth in a post-pandemic world. MongoDB's latest quarterly report has left analysts scrambling to assess the durability of Atlas demand, the company's cloud-based database service. The numbers look impressive: 30% revenue growth and a 91% increase in remaining performance obligations (RPO). However, concerns about the sustainability of this growth begin to emerge when examined closer. The disparity between Atlas and Enterprise Advanced revenue is striking. While Atlas expanded by 29%, Enterprise Advanced and other revenue grew at a rate of 36%. This raises questions about the underlying drivers of MongoDB's growth: Is it the company's ability to scale its infrastructure and research costs more slowly than revenue, or is there something more fundamental at play? MongoDB's total customers have increased by over 11,000 since last year, with Atlas customers reaching a staggering 69,300. Yet, what does this mean for the company's long-term prospects? Will the market continue to support this level of growth, or will the inevitable slowdown in enterprise spending take its toll? Historically, MongoDB has been at the forefront of the cloud-first movement in databases. Its Atlas platform has disrupted traditional database providers like Oracle and Microsoft, attracting a new generation of developers who value flexibility and scalability. However, as the market continues to evolve, MongoDB faces increasing competition from newer players like Snowflake and Cockroach Labs. A potential concern is that MongoDB's RPO growth may not necessarily translate to revenue growth in the same period. The company has raised its fiscal 2027 guidance to $2.99 billion to $3.03 billion, but there are no guarantees this will materialize. The market has been known to be unforgiving when it comes to overpromising and underdelivering. MongoDB's decision to expand search and vector-search capabilities across cloud, private-cloud, and self-managed environments takes on new significance in this context. By investing in these areas, the company is betting that its customers will continue to demand more from their database providers. However, whether this will be enough to sustain growth in a post-pandemic world, where enterprise spending is under increasing pressure, remains uncertain. The answer lies not just with MongoDB but with broader market trends shaping the industry. As companies like Snowflake and Cockroach Labs gain traction, it's clear that the database landscape is becoming increasingly complex. MongoDB must navigate this new reality while continuing to innovate and disrupt. Ultimately, the question of Atlas demand durability hangs in the balance. Will MongoDB be able to sustain its growth momentum, or will the market prove too unforgiving? Only time will tell, but one thing is certain: the company's future depends on it. The coming quarters will be crucial for MongoDB as it continues to navigate this new landscape. Its ability to deliver on promises and sustain growth momentum will be put to the test, and the stakes have never been higher for this once-promising cloud-first database provider. Reader views. * TS The Stack Desk · editorial The Atlas growth numbers are indeed impressive, but let's not get too caught up in the excitement just yet. A closer look at MongoDB's balance sheet reveals that the company is still heavily dependent on upfront payments from customers, which can create volatility in revenue recognition. This could be a concern if Atlas adoption starts to slow down or if the company faces increased competition in the market. It's time for investors to start digging deeper into the financials and separating hype from substance. * AK Asha K. · self-taught dev The elephant in the room is MongoDB's customer mix: 69,300 Atlas customers versus a paltry 11,000 Enterprise Advanced customers. Can this model sustain itself? The answer lies in how well MongoDB can upsell and cross-sell its Atlas users into more lucrative offerings. Its aggressive growth strategy may be built on shaky ground if it fails to close the gap between these two segments. * QS Quinn S. · senior engineer The Atlas dilemma is indeed a tricky one for MongoDB. While the numbers look great on paper, there's more to consider here than just revenue growth and customer count. The fact that Enterprise Advanced revenue outpaced Atlas by 7% raises questions about whether Atlas is truly driving this growth or if it's just a byproduct of the company's aggressive expansion into cloud services. As the market continues to evolve, MongoDB will need to show that its Atlas platform can not only keep pace but also continue to innovate and adapt to changing customer needs.

Cockroach Labs
Jul 7th, 2026
How CockroachDB and IBM LinuxONE Rockhopper 5 power Resilient AI infrastructure.

How CockroachDB and IBM LinuxONE Rockhopper 5 power Resilient AI infrastructure. Published on July 7, 2026 Why does AI require a new approach to infrastructure? AI is changing enterprise infrastructure requirements by increasing demand for continuous data availability, high concurrency, and real-time decision-making. Customers expect uninterrupted experiences, and AI-driven systems depend on continuous, reliable access to current data. Even a few minutes of downtime can result in significant financial and reputational loss. As Cockroach Labs CEO Spencer Kimball CEO recently observed, "The tsunami of autonomous agents has arrived." Supporting those systems requires elastic infrastructure and software that can seamlessly scale and work together. Always-on infrastructure is becoming a prerequisite for enterprise AI. As organizations deploy AI assistants, autonomous workflows, and agentic applications into production, the underlying data platform must deliver consistent access to current data while scaling to unpredictable demand. From real-time payments to AI-driven applications, enterprises rely on critical services such as digital banking and wallets, payment processing, trading and order management, and identity and access management (IAM). IBM LinuxONE is IBM's enterprise-class Linux platform, designed for extreme reliability, security, and performance trusted by industries where downtime is not an option. CockroachDB's distributed SQL and integrated vector search capabilities provide the data foundation required for AI applications, supporting semantic retrieval, embeddings, agent memory, and transactional consistency. LinuxONE Rockhopper 5 delivers the resilient, secure, and scalable infrastructure needed to run those workloads in production. Why traditional infrastructure falls short for AI workloads. Traditional infrastructure was not designed for the scale, availability, and concurrency requirements of modern AI workloads. Commodity infrastructure fails frequently, and databases are forced to compensate with complex failover and recovery mechanisms. This leads to higher costs, increased operational burden, and systems that are reactive rather than resilient. Additionally, these systems scale linearly and lack true distributed capabilities. When operations and engineering teams try to address resilience, scale, and performance with disjointed point solutions, the result is disparate data sprawl with complex IT management capabilities. Beyond increasing operational overhead, fragmented architectures can slow application delivery and make it harder for teams to introduce new AI capabilities with confidence. Consolidating infrastructure and data services helps organizations reduce complexity while improving operational agility as workloads evolve. What is the Always-On Data Foundation? The Always-On Data Foundation combines CockroachDB and IBM LinuxONE Rockhopper 5 to provide a resilient data platform for enterprise AI and mission-critical workloads. Today, Cockroach Labs and IBM introduce this integrated architecture, powered by the newly announced LinuxONE Rockhopper 5. Replacing fragmented stacks with a tightly integrated combination of enterprise infrastructure and distributed SQL, this solution supports continuous availability and seamless elasticity. When database software is fundamentally aware of, and optimized for, its underlying hardware, it can intelligently distribute workloads to maximize resilience and throughput. This solution is purpose-built for enterprise AI workloads where infrastructure doesn't just support workloads, it actively enables intelligent, autonomous systems. The platform is engineered to meet the demands of real-time AI and agentic workloads. Vector Search Meets Distributed SQL for AI Workloads - AI applications need more than a resilient data layer: They need one that can handle semantic search, embeddings, and real-time vector retrieval alongside transactional data. This guide explores how distributed SQL enables unified AI data architecture without the complexity of managing separate vector stores. CockroachDB on LinuxONE Rockhopper 5 embeds AI-readiness directly into the foundation. By tightly integrating enterprise infrastructure with distributed SQL, it creates a system where the database is not just distributed but intelligent and context-aware. It is optimized to take advantage of the underlying hardware it runs on, and dynamically optimizes workload placement to ensure that AI models and agents always have fast, reliable access to data. The converged platform provides a resilient foundation for distributed AI workloads that require both continuous availability and transactional consistency. Rather than treating resilience as a separate operational concern, infrastructure and the database work together to help support reliable application behavior under changing demand. In the agentic era. AI agents are not passive; they continuously observe, decide, and act. They require: * Massive concurrency to operate at scale * Global consistency to make accurate decisions * Zero-downtime execution to avoid disruption in real-time processes The distributed SQL foundation for agentic scale - Agentic systems don't just need more compute, they need a data layer built to handle continuous, concurrent, autonomous activity at scale. Watch this webinar to see how distributed SQL meets the unique demands of agentic AI in production. What makes this architecture different? Combining enterprise infrastructure with distributed SQL removes traditional tradeoffs between resilience, scalability, and operational complexity. It's not about improving uptime, but removing downtime as a design concern. LinuxONE Rockhopper 5 and CockroachDB eliminate the trade-offs of traditional architectures by co-designing reliability into every layer: * Hardware designed to avoid failure: LinuxONE Rockhopper 5 Express brings highly efficient, enterprise-grade reliability (99.999999% availability) into an accessible form factor to consolidate systems and reduce physical failure rates. * Database designed to survive failure: CockroachDB operates as a natively distributed SQL layer, ensuring seamless elasticity and continuous availability even when regional disruptions occur. Ready for the agentic era. This hardware-software synergy eliminates traditional bottlenecks, delivering the real-time consistency and hyper-concurrency autonomous AI agents demand. This is not theoretical; it's the exact architecture, currently: * Scaling AI to handle trillions of objects * Controlling agent and data access for hundreds of millions of users * Powering mission-critical AI solutions designed to streamline efficiency Building resilient AI infrastructure across hybrid cloud. Resilient AI infrastructure depends on keeping applications close to their data while maintaining consistency across hybrid cloud, on-premises, and edge environments. This integrated foundation anchors a strategic hybrid cloud and data platform strategy. By deploying CockroachDB's natively distributed, PostgreSQL-compatible data services across the LinuxONE portfolio, organizations can position infrastructure and software directly adjacent to their applications. Historically, bridging on-premises environments, public clouds, and the edge meant accepting severe tradeoffs between latency, consistency, and security. This architecture eliminates those compromises, allowing enterprises to push compute and data closer to the application layer. It drastically reduces latency for real-time AI and agentic workflows, while maintaining strict global consistency and data sovereignty. CockroachDB runs on LinuxONE systems, including LinuxONE Rockhopper 5, to automatically distribute and replicate data across nodes and regions. The result is a system that's not just distributed, but intelligent and context-aware, dynamically optimizing workload placement to ensure AI agents have fast, reliable, and consistent access to data, even during site-level failures. Organizations gain the flexibility to modernize applications and execute high-concurrency AI initiatives securely on a unified and trusted infrastructure. As AI initiatives move from experimentation into production, resilient data infrastructure becomes a strategic advantage rather than simply an operational requirement. Organizations that can maintain consistent performance, continuous availability, and global data consistency are better positioned to deploy AI applications with confidence while supporting long-term business growth. Related announcement. Get started with CockroachDB on IBM LinuxONE. If downtime impacts your business, it's time to rethink the data infrastructure that supports it. Partner with IBM and Cockroach Labs to build resilient, secure, always-on platforms on LinuxONE Rockhopper 5. Learn how CockroachDB and IBM LinuxONE power resilient AI infrastructure. Contact Kyle Basile, Sr. Partner Sales Manager, IBM, at Cockroach Labs, [email protected]. Kyle Basile is Sr. Partner Sales Manager, IBM, at Cockroach Labs. Work With Me will email you updates about CockroachDB. You can unsubscribe at any time. 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