Neha Narkhede
Co-founder & CEO, Oscilar. On 2 shows, 2 appearances. The Shows tab opens the full record on each.
founderexecutiveengineerinvestorauthor@nehanarkhede ↗LinkedIn ↗nehanarkhede.com ↗Wikipedia ↗
She co-created the open-source event-streaming platform Apache Kafka at LinkedIn and co-founded Confluent, where she served as CTO and CPO. She is currently the co-founder and CEO of Oscilar, an AI-powered fraud prevention and risk decisioning platform, and actively invests in startups.
2shows
2appearances
33statements
5resolved
3supported
1contradicted
60%fully supported
2said about them ↓ Everything Neha Narkhede said on any show that made the record, most notable first. Each card names its show and opens the statement there.
Narkhede: Confluent ignored narrow ICPs to capture the broad Kafka base
“Kafka, you know, that was one of the reasons why we couldn't or we didn't sort of narrowly focus on an ICP like traditional companies do for good reason. It was because, you know, the Kafka adoption base was so broad and for Confluent to quickly convert those …”
Narkhede: Commercial open-source requires all project creators to found together
“For the success of an open source company, all the creators should be part of it. And when that doesn't happen, you have two companies and they're competing on things they shouldn't be competing on, which mostly comes down to pricing and it's just a race to th…”
Narkhede: Confluent chose not to separate on-prem and cloud sales teams
“We actually decided to not split it. And that was because we ultimately wanted to transition to a cloud first business. So we put in a, instead a lot of thought and a lot of investment in sales enablement you know, internal education of why this is important, …”
Narkhede: Confluent probably would have failed if it started as SaaS-only
“Would it have just been feasible if we started with a SaaS only offering? And the answer is probably not because, you know, one of the most important things an open source company needs to do is quickly establish yourself as the market leader, quickly establis…”
Narkhede: Central streaming platforms like Kafka replace legacy enterprise service buses
“Fundamentally, companies want to collect all sorts of data, and there isn't just a database and a warehouse anymore. There are lots and lots of distributed systems, which means that we need to move to a sort of platform-centric approach, and this will, this is…”
Narkhede: Stream processing behaves like microservices, not faster MapReduce jobs
“What we learned is that, ah, stream processing is in fact much more than a faster MapReduce layer. It, in fact, most of the applications that do stream processing look much more like a microservice of an application, and less like a faster version of a batch o…”
Narkhede: Kafka was used by 50% of Fortune 500 when Confluent launched
“Confluent kind of started with a proven technology that was used at, you know, roughly 50% of Fortune 500 companies at that point in time.”
Narkhede: Transitioning enterprise sales to consumption models is the hardest challenge
“Sales was just a whole different, you know, dynamic. It was The most difficult one to solve for because in the early days, you know, if you're offering a software product, you have the traditional salespeople who are used to selling a subscription-based softwa…”
Narkhede: Confluent relicensed add-ons to stop cloud vendors reselling managed services
“So we introduced value-added offerings like stream processing, KSQL, under licenses that were similar, very similar in spirit to the open source friendly Apache two dot O, but these licenses had specific provisions that prevented other entities from just offer…”
Neha Narkhede: All enterprise data can be represented as event streams
“My bold claim here is that all your data can be represented as event streams.”
Narkhede: Non-Kafka stream processing systems are complex and limited to niche problems
“Kafka Streams is, Extremely powerful, but very simple because it builds on top of primitives in Kafka. A lot of other systems are powerful, but, ah, not so simple. They're only applicable to a niche set of problems.”
Narkhede: Operational ease is the right starting point for open-source companies
“The first one was operational ease, you know, offering tools and enhancements to simplify the deployment, management, and scaling of Kafka clusters, which is actually, I think, the right starting point for many open source companies.”
Narkhede: Competing against a thought leader is harder than product-level competition
“I think what differentiates the top 20% from the rest is thought leadership. You know, thinking of develop developer evangelism as one of the most important tools to establish yourself as the thought leader in the space, because that is actually a core differe…”
Narkhede: Features enabling end users should remain open source
“Features that directly
Enabled the end users of the open source product.
We believe should ideally remain open source or be open source.”
Narkhede: Confluent never split engineering teams between cloud and on-prem
“We kept the foundational teams the same. So there was only one team ever working on Apache Kafka and the foundation. There was only one team that was ever developing a specific proprietary feature set. So we never split, you know, specific teams or individual …”
Narkhede: Oscilar targets risk executives because they lack in-house engineering teams
“In Austin, I realized that the head of risk, which is the buyer, actually does not have the engineering team. They just don't hire for it. They don't report into it. They just don't have the team that can build the technology and the product they want. So they…”
Narkhede: MongoDB Atlas is arguably the most successful cloud product
“And back then I remember that the CPO of MongoDB and today Atlas, their product is the most successful cloud product out there, arguably.”
Narkhede: Companies are shifting from batch processing to real-time data
“A lot of companies are making a fundamental shift towards leveraging data in real-time, and moving away from that style computing Ah, which is essentially once a day data processing.”
Neha Narkhede: Stream processing generalizes request-response and batch paradigms
“Stream processing is often thought about as something that is just real time in nature, but it is really a generalization of these two extremes, request, response, and batch.”
Narkhede: Banks are leading non-tech enterprise adoption of Apache Kafka
“In fact, banks is are definitely leading the way in terms of putting Kafka To you know, very sort of ambitious applications.”
Narkhede: Confluent was founded four years after Kafka was open-sourced
“So this conference started four years after Apache Kafka was open sourced and became successful and
It was very much an organic decision.”
Narkhede: Confluent initiated SaaS product two years in
“So about two years in, we realized that there must be a SaaS offering because at that time, the whole industry was in the middle of this transition from on-prem environments to the public cloud.”
Narkhede: Confluent Cloud is nearly larger than its on-premise software business
“And today, our cloud business is growing and is, you know, almost larger than the software business as well.”
The other half of the tape: Neha Narkhede's own voice is left out of every number here. Other people bring the name up 2 times in 2 episodes across the shows. every mention, with the transcript →
Who brings them up most Mike Volpi 1Jay Kreps 1
Every mention by year
tap a year for its mentions
the MAD Podcast 1
In Depth 1
2026 1 mention in 1 episode
One line per show, most statements first. The link opens Neha's full record on that show: the calibration, argument clarity, speaking style and every statement made there.
| Show | Role there | Eps | Statements | Record | |
|---|---|---|---|---|---|
| IN DEPTHLEDGER | Co-founder & CEO, Oscilar | 1 | 24 | 33% 1/3 | full record on In Depth → |
| MADLEDGER | Co-founder & CEO, Oscilar | 1 | 9 | 100% 2/2 | full record on the MAD Podcast → |