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StreamSets Raises $35 Million in Series C Funding

StreamSets raised $35 million in a Series C funding round, led by Harmony Partners.

Also participating in this round are new investor Tenaya Capital, and existing investors Battery Ventures and New Enterprise Associates (NEA). This round brings the firm’s total funding to over $65 million. StreamSets will use the investment to accelerate its international go-to-market, research and development efforts, and customer-facing functions.

The investment underscores the growing importance of DataOps, the emerging practice of applying DevOps principles to data management and data integration. DataOps has grown in importance as companies re-architect their “data supply chain” with microservices; leverage new data sources like IoT devices, API feeds and systems logs; and adopt an array of modern data platforms such as AWS, Microsoft Azure, Google Cloud Platform, Apache Kafka, Apache Hadoop/Spark, and NoSQL.

StreamSets DataOps Platform lets enterprises build, integrate, deploy and operate dataflow architectures for big data and streaming applications — all as a continuous, disciplined process. They often realize order-of-magnitude cost savings and greatly accelerate the delivery of data serving key initiatives such as customer 360, cybersecurity and IoT. The platform’s unique ability to inspect and act on data as it flows (“Intelligent Pipelines”) means it can automatically address data drift to avoid pipeline breakdowns, detect and protect sensitive data in-stream, and enforce Data SLA guarantees — things that are not possible using traditional data integration solutions.

“We’re seeing enterprise data architectures grow in complexity while use of big and fast data becomes business-critical, driving market insights, product innovation and operational excellence,” said Mark Lotke, founder and managing partner, Harmony Partners. “Harmony is purpose-built to find and support bold tech entrepreneurs who are revolutionizing their industries, having invested in firms such as Alation, InfluxDB and Qubole. StreamSets fundamentally changes the $10 billion data integration market, helping companies cost-effectively squeeze maximum value out of their big data and streaming data assets.”

“The disruptive trends of cloud data platforms, self-service analytics and open source software allow enterprises to unleash the power of big and fast data to all business units and processes,” said Girish Pancha, CEO and co-founder, StreamSets. “Companies and government entities use the StreamSets DataOps Platform to operationalize the continuous delivery of the right data to the right people, even as data sources, platforms and user requirements constantly change. Built for modern enterprise architectures, StreamSets technology does away with the rigidity and opaqueness of traditional data integration software.”

“Battery has had a long-standing thesis that data and AI are the key enablers of digital transformation across many industries,” said Dharmesh Thakker, a Battery Ventures general partner and StreamSets board member. “We have enjoyed our partnership with StreamSets from the company’s early days, as they have become a new data integration standard in a cloud- and AI-first world. We are excited to partner with Harmony, Tenaya and NEA to drive the next stage of the company’s growth.”

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StreamSets Raises $35 Million in Series C Funding

StreamSets raised $35 million in a Series C funding round, led by Harmony Partners.

Also participating in this round are new investor Tenaya Capital, and existing investors Battery Ventures and New Enterprise Associates (NEA). This round brings the firm’s total funding to over $65 million. StreamSets will use the investment to accelerate its international go-to-market, research and development efforts, and customer-facing functions.

The investment underscores the growing importance of DataOps, the emerging practice of applying DevOps principles to data management and data integration. DataOps has grown in importance as companies re-architect their “data supply chain” with microservices; leverage new data sources like IoT devices, API feeds and systems logs; and adopt an array of modern data platforms such as AWS, Microsoft Azure, Google Cloud Platform, Apache Kafka, Apache Hadoop/Spark, and NoSQL.

StreamSets DataOps Platform lets enterprises build, integrate, deploy and operate dataflow architectures for big data and streaming applications — all as a continuous, disciplined process. They often realize order-of-magnitude cost savings and greatly accelerate the delivery of data serving key initiatives such as customer 360, cybersecurity and IoT. The platform’s unique ability to inspect and act on data as it flows (“Intelligent Pipelines”) means it can automatically address data drift to avoid pipeline breakdowns, detect and protect sensitive data in-stream, and enforce Data SLA guarantees — things that are not possible using traditional data integration solutions.

“We’re seeing enterprise data architectures grow in complexity while use of big and fast data becomes business-critical, driving market insights, product innovation and operational excellence,” said Mark Lotke, founder and managing partner, Harmony Partners. “Harmony is purpose-built to find and support bold tech entrepreneurs who are revolutionizing their industries, having invested in firms such as Alation, InfluxDB and Qubole. StreamSets fundamentally changes the $10 billion data integration market, helping companies cost-effectively squeeze maximum value out of their big data and streaming data assets.”

“The disruptive trends of cloud data platforms, self-service analytics and open source software allow enterprises to unleash the power of big and fast data to all business units and processes,” said Girish Pancha, CEO and co-founder, StreamSets. “Companies and government entities use the StreamSets DataOps Platform to operationalize the continuous delivery of the right data to the right people, even as data sources, platforms and user requirements constantly change. Built for modern enterprise architectures, StreamSets technology does away with the rigidity and opaqueness of traditional data integration software.”

“Battery has had a long-standing thesis that data and AI are the key enablers of digital transformation across many industries,” said Dharmesh Thakker, a Battery Ventures general partner and StreamSets board member. “We have enjoyed our partnership with StreamSets from the company’s early days, as they have become a new data integration standard in a cloud- and AI-first world. We are excited to partner with Harmony, Tenaya and NEA to drive the next stage of the company’s growth.”

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In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...