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Arjun Narayan

Venture Partner, Amplify Partners · 1 appearance on the record.

computed by AI from the episodes · how this works → · full disclaimer →

founderinvestorexecutiveengineerscientist@narayanarjun ↗LinkedIn ↗arjunnarayan.com ↗

Arjun Narayan co-founded the streaming database startup Materialize in 2019 and served as its founding CEO before transitioning into venture capital with Amplify Partners. He holds a Ph.D. in computer science from the University of Pennsylvania and previously worked on SQL query execution at Cockroach Labs.

9statements → 5claims → 1claims resolved → 3.56/5average certainty → 2.33/5average debate potential → 4.5/5argument clarity · the sources → 1said about them ↓

1 supported 0 partly supported 0 contradicted 4 not checkable as stated how the 5 claims stand · each chip opens the sources

1 prediction · 4 assertions · 2 opinions · 2 insights · every statement was checked. The prediction and assertions are the 5 claims: statements the public record can support or contradict. 1 is resolved, and 4 name no date, number or outcome precise enough to check. Everything else (opinions, insights, what ifs, disclosures) can never be settled by the record, so it carries no assessment.

The record, in short

What the tape says about how Arjun argues and how the claims held up. Everything they said, and everything said about them, is in the tabs below.

Their most notable supported claim

Assertion Supported
Narayan: Timely Dataflow was first stream processor to match batch processing capabilities
“It was sort of the first, what I would describe as The very first stream processor that could do everything that batch processors could do.”
Arjun Narayan Mar 15, 2021 ▶ 13:13 Fireside Chat: Arjun Narayan (Founder & CEO, Materialize) with Matt Turck (Partner, FirstMark)

Argument clarity: do they answer the question? how? →

4.5 / 5 directness 5 · coherence 4.9 · precision 4.4 · compression 4

answered every one of 8 assessed questions directly

This is a score against a rubric. It is not a rank. Every host question → answer exchange is scored with names hidden on directness, coherence, precision and compression, 1–5 each, on meaning alone: disfluencies are ignored, and only raw unedited episodes count. This is the score that measures thought. Every scored exchange, scores shown → · The rubric and its checks →

How they sound: speaking style how? →

216 words/min while actually speaking · 38.1 um and uh per 1k words

Measured by listening to the audio itself: 3,467 words across 1 episode of raw-level tape, transcribed verbatim with every um and uh kept, each one attributed only where the alignment onto our timed stream is unambiguous. These are measurements of speaking style. We do not rank them: across this corpus, fluency and argument quality are nearly uncorrelated (ρ≈0.2), and smooth talking does not signal clear thinking. How it's measured →

Everything Arjun Narayan said on the MAD Podcast that made the record, most notable first. Filter by type, assessment or year in the ledger →

Assertion Not checkable as stated
Narayan: Materialize provides 99.9% of batch database functionality
“And we really think materialize the product is the first database that gives you know, I don't want to say literally all the functionality, but to the morally speaking, you know, 99.9% of the functionality that you can write in a batch database.”
Arjun Narayan Mar 15, 2021 ▶ 18:13 Fireside Chat: Arjun Narayan (Founder & CEO, Materialize) with Matt Turck (Partner, FirstMark)
Prediction Not checkable as stated
Narayan: Streaming will remain niche until tooling matches batch systems
“Until streaming gets to the same level of tooling, and a large part of that tooling is dbt as existing batch systems you know, it will still remain a fairly niche technology.”
Arjun Narayan Mar 15, 2021 ▶ 21:17 Fireside Chat: Arjun Narayan (Founder & CEO, Materialize) with Matt Turck (Partner, FirstMark)
Insight
Narayan: Software requiring code rewrites in new languages is largely doomed
“Any pitch. I'm generally very skeptical where you can tell folks, you can have all these great new benefits of low latency or whatever it is, but you got to start all over from scratch, right? You have to throw everything out there and you're going to rebuild …”
Arjun Narayan Mar 15, 2021 ▶ 7:37 Fireside Chat: Arjun Narayan (Founder & CEO, Materialize) with Matt Turck (Partner, FirstMark)
Assertion Supported
Narayan: Timely Dataflow was first stream processor to match batch processing capabilities
“It was sort of the first, what I would describe as The very first stream processor that could do everything that batch processors could do.”
Arjun Narayan Mar 15, 2021 ▶ 13:13 Fireside Chat: Arjun Narayan (Founder & CEO, Materialize) with Matt Turck (Partner, FirstMark)
Assertion Not checkable as stated
Arjun Narayan: Streaming data processing has expanded beyond niche financial applications
“And what we've been seeing is that streaming has started to become over the, over several decades and particularly in the past few years, much, much more broadly applicable. Beyond those small niche use cases as more and more businesses and use users benefit f…”
Arjun Narayan Mar 15, 2021 ▶ 1:24 Fireside Chat: Arjun Narayan (Founder & CEO, Materialize) with Matt Turck (Partner, FirstMark)
Insight
Narayan: Apache Kafka is essential for building and operating microservices
“It has been to, in my opinion, a key enabler of microservices. I think it's pretty difficult to build and operate a decentralized set of microservices without first adopting something like Kafka in your organization to just move the data between all of these v…”
Arjun Narayan Mar 15, 2021 ▶ 4:25 Fireside Chat: Arjun Narayan (Founder & CEO, Materialize) with Matt Turck (Partner, FirstMark)
Assertion Not checkable as stated
Arjun Narayan: Standard analytics databases add latency by lacking incremental computation
“So, so stopping everything and recomputing from scratch is not really a framework that scales to these lower and lower latencies, which is why fundamentally a lot of analytics databases today including some of the more famous ones, they would prefer it if you …”
Arjun Narayan Mar 15, 2021 ▶ 5:45 Fireside Chat: Arjun Narayan (Founder & CEO, Materialize) with Matt Turck (Partner, FirstMark)
Opinion
Arjun Narayan: Snowflake succeeded by wrapping cloud architecture in familiar SQL
“Snowflake is a fantastic example of, under the hood, they, you know, they have a very modern microservice architecture, but it's all sort of very neatly wrapped up with a bow on top, such that it looks like a SQL database, and that's much, much more attractive…”
Arjun Narayan Mar 15, 2021 ▶ 11:20 Fireside Chat: Arjun Narayan (Founder & CEO, Materialize) with Matt Turck (Partner, FirstMark)
Opinion
Narayan: dbt serves as GitHub for SQL code
“I think of it as like GitHub for all of your SQL, right?”
Arjun Narayan Mar 15, 2021 ▶ 19:58 Fireside Chat: Arjun Narayan (Founder & CEO, Materialize) with Matt Turck (Partner, FirstMark)

The other half of the tape: Arjun Narayan's own voice is left out of every number here. Other people bring the name up 1 time in 1 episode on the MAD Podcast. every mention, with the transcript →

Who brings them up most Chip Huyen 1

Every mention by year

tap a year for its mentions
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0112021episodes it came up in
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2021 1 mention in 1 episode

Appearances (1)

EpisodeDateSpeaking time
Fireside Chat: Arjun Narayan (Founder & CEO, Materialize) with Matt Turck (Partner, FirstM Mar 15, 2021 19m
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