Dec 5, 2013 · 44m · mad

Panel discussion // Data Driven NYC #13 // Dec 2012

Oren (Sqrrl) · 9m spoken Eric (MemSQL) · 8m spoken Drew (InfoChimps) · 8m spoken Matt Turck · 3m spoken Alexander Younghoff · 1m spoken Joseph Adler · 1m spoken Charles Amor · 1m spoken Carter Schoenwald · 50s spoken Benjamin Swamy · 30s spoken Matthew Rutley · 26s spoken Mandeep Singh · 21s spoken
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gold bands on the timeline = statements, start to end. Hover to read, click to jump. CC turns on captions

At Data Driven NYC #13, host Matt Turck moderates a panel featuring founders Oren Falkowitz (Sqrrl), Drew Bansal (InfoChimps), and Eric Frenkiel (MemSQL) discussing startup origins, database architectures, enterprise security, and the future of big data.

How this conversation actually went

Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. Matt holds 8.3% of the talking time here. How this is scored →

Matt as informed peer 1.7 Guest teaching 2.8 Guest disagreement 1.7 Matt pushing back 1.0
05100:0015:0030:000:36–7:50 · Matt as informed peer 1/10 Panelist Origins and Company Evolution Matt opens the panel with lightweight origin questions about the founders' transitions into entrepreneurship. Oren playfully corrects Matt's narrative about VCs forcing Sqrrl to relocate to Boston.7:50–9:53 · Matt as informed peer 1/10 MemSQL Stealth Development and In-Memory Architecture An audience member asks about MemSQL's stealth period, prompting Eric to explain the technical necessity of building an in-memory database from scratch. The host acts purely as a facilitator passing the microphone.9:53–12:26 · Matt as informed peer 3/10 Open Source vs. Proprietary Database Models Matt prompts a debate on open-source versus proprietary models and interjects to note that complex database software is frequently open-sourced. Eric argues open source is a great marketing tool but a poor business model.12:26–18:42 · Matt as informed peer 4/10 Database Paradigms: NoSQL vs. NewSQL Matt questions whether NoSQL and NewSQL vendors compete directly and asks about enterprise cloud adoption across industry verticals. The guests explain how relational models are evolving past NoSQL key-value limitations.18:42–22:08 · Matt as informed peer 1/10 Audience Q&A: Security Policies and Unstructured Data Audience members inquire about enterprise security standards and unstructured data capabilities. Oren explains how fine-grained security policies can be embedded directly into database keys.22:08–28:04 · Matt as informed peer 1/10 Audience Q&A: Data Locality and Enterprise Compliance Audience questions focus on memory locality and enterprise compliance. Oren uses a colorful analogy comparing specialized extreme performance tools to a Formula One car versus ten thousand versatile Kias.28:04–35:41 · Matt as informed peer 1/10 Audience Q&A: Shared-Nothing Architecture and SQL vs. MongoDB Audience members challenge panelists on shared-nothing architectures, data marketplace value, and SQL versus MongoDB relevance. Eric details MongoDB's performance constraints, including its global write lock.35:41–38:30 · Matt as informed peer 1/10 Audience Q&A: Data Obsolescence and Multi-Database Architectures An audience member asks about handling data obsolescence over time. Drew outlines how enterprise platforms tier data storage dynamically based on time horizons.38:30–42:32 · Matt as informed peer 2/10 Audience Q&A: Network Inventions and Ethics in Big Data An audience member proposes an unfocused question about a nation-scale GPS invention, prompting Matt to firmly step in and redirect the discussion offline. Drew then shares thoughts on big data ethics and privacy.0:36–7:50 · Guest teaching 2/10 Panelist Origins and Company Evolution Matt opens the panel with lightweight origin questions about the founders' transitions into entrepreneurship. Oren playfully corrects Matt's narrative about VCs forcing Sqrrl to relocate to Boston.7:50–9:53 · Guest teaching 2/10 MemSQL Stealth Development and In-Memory Architecture An audience member asks about MemSQL's stealth period, prompting Eric to explain the technical necessity of building an in-memory database from scratch. The host acts purely as a facilitator passing the microphone.9:53–12:26 · Guest teaching 3/10 Open Source vs. Proprietary Database Models Matt prompts a debate on open-source versus proprietary models and interjects to note that complex database software is frequently open-sourced. Eric argues open source is a great marketing tool but a poor business model.12:26–18:42 · Guest teaching 4/10 Database Paradigms: NoSQL vs. NewSQL Matt questions whether NoSQL and NewSQL vendors compete directly and asks about enterprise cloud adoption across industry verticals. The guests explain how relational models are evolving past NoSQL key-value limitations.18:42–22:08 · Guest teaching 2/10 Audience Q&A: Security Policies and Unstructured Data Audience members inquire about enterprise security standards and unstructured data capabilities. Oren explains how fine-grained security policies can be embedded directly into database keys.22:08–28:04 · Guest teaching 3/10 Audience Q&A: Data Locality and Enterprise Compliance Audience questions focus on memory locality and enterprise compliance. Oren uses a colorful analogy comparing specialized extreme performance tools to a Formula One car versus ten thousand versatile Kias.28:04–35:41 · Guest teaching 4/10 Audience Q&A: Shared-Nothing Architecture and SQL vs. MongoDB Audience members challenge panelists on shared-nothing architectures, data marketplace value, and SQL versus MongoDB relevance. Eric details MongoDB's performance constraints, including its global write lock.35:41–38:30 · Guest teaching 3/10 Audience Q&A: Data Obsolescence and Multi-Database Architectures An audience member asks about handling data obsolescence over time. Drew outlines how enterprise platforms tier data storage dynamically based on time horizons.38:30–42:32 · Guest teaching 2/10 Audience Q&A: Network Inventions and Ethics in Big Data An audience member proposes an unfocused question about a nation-scale GPS invention, prompting Matt to firmly step in and redirect the discussion offline. Drew then shares thoughts on big data ethics and privacy.0:36–7:50 · Guest disagreement 1/10 Panelist Origins and Company Evolution Matt opens the panel with lightweight origin questions about the founders' transitions into entrepreneurship. Oren playfully corrects Matt's narrative about VCs forcing Sqrrl to relocate to Boston.7:50–9:53 · Guest disagreement 1/10 MemSQL Stealth Development and In-Memory Architecture An audience member asks about MemSQL's stealth period, prompting Eric to explain the technical necessity of building an in-memory database from scratch. The host acts purely as a facilitator passing the microphone.9:53–12:26 · Guest disagreement 2/10 Open Source vs. Proprietary Database Models Matt prompts a debate on open-source versus proprietary models and interjects to note that complex database software is frequently open-sourced. Eric argues open source is a great marketing tool but a poor business model.12:26–18:42 · Guest disagreement 2/10 Database Paradigms: NoSQL vs. NewSQL Matt questions whether NoSQL and NewSQL vendors compete directly and asks about enterprise cloud adoption across industry verticals. The guests explain how relational models are evolving past NoSQL key-value limitations.18:42–22:08 · Guest disagreement 1/10 Audience Q&A: Security Policies and Unstructured Data Audience members inquire about enterprise security standards and unstructured data capabilities. Oren explains how fine-grained security policies can be embedded directly into database keys.22:08–28:04 · Guest disagreement 2/10 Audience Q&A: Data Locality and Enterprise Compliance Audience questions focus on memory locality and enterprise compliance. Oren uses a colorful analogy comparing specialized extreme performance tools to a Formula One car versus ten thousand versatile Kias.28:04–35:41 · Guest disagreement 3/10 Audience Q&A: Shared-Nothing Architecture and SQL vs. MongoDB Audience members challenge panelists on shared-nothing architectures, data marketplace value, and SQL versus MongoDB relevance. Eric details MongoDB's performance constraints, including its global write lock.35:41–38:30 · Guest disagreement 1/10 Audience Q&A: Data Obsolescence and Multi-Database Architectures An audience member asks about handling data obsolescence over time. Drew outlines how enterprise platforms tier data storage dynamically based on time horizons.38:30–42:32 · Guest disagreement 2/10 Audience Q&A: Network Inventions and Ethics in Big Data An audience member proposes an unfocused question about a nation-scale GPS invention, prompting Matt to firmly step in and redirect the discussion offline. Drew then shares thoughts on big data ethics and privacy.0:36–7:50 · Matt pushing back 1/10 Panelist Origins and Company Evolution Matt opens the panel with lightweight origin questions about the founders' transitions into entrepreneurship. Oren playfully corrects Matt's narrative about VCs forcing Sqrrl to relocate to Boston.7:50–9:53 · Matt pushing back 0/10 MemSQL Stealth Development and In-Memory Architecture An audience member asks about MemSQL's stealth period, prompting Eric to explain the technical necessity of building an in-memory database from scratch. The host acts purely as a facilitator passing the microphone.9:53–12:26 · Matt pushing back 2/10 Open Source vs. Proprietary Database Models Matt prompts a debate on open-source versus proprietary models and interjects to note that complex database software is frequently open-sourced. Eric argues open source is a great marketing tool but a poor business model.12:26–18:42 · Matt pushing back 2/10 Database Paradigms: NoSQL vs. NewSQL Matt questions whether NoSQL and NewSQL vendors compete directly and asks about enterprise cloud adoption across industry verticals. The guests explain how relational models are evolving past NoSQL key-value limitations.18:42–22:08 · Matt pushing back 0/10 Audience Q&A: Security Policies and Unstructured Data Audience members inquire about enterprise security standards and unstructured data capabilities. Oren explains how fine-grained security policies can be embedded directly into database keys.22:08–28:04 · Matt pushing back 1/10 Audience Q&A: Data Locality and Enterprise Compliance Audience questions focus on memory locality and enterprise compliance. Oren uses a colorful analogy comparing specialized extreme performance tools to a Formula One car versus ten thousand versatile Kias.28:04–35:41 · Matt pushing back 0/10 Audience Q&A: Shared-Nothing Architecture and SQL vs. MongoDB Audience members challenge panelists on shared-nothing architectures, data marketplace value, and SQL versus MongoDB relevance. Eric details MongoDB's performance constraints, including its global write lock.35:41–38:30 · Matt pushing back 0/10 Audience Q&A: Data Obsolescence and Multi-Database Architectures An audience member asks about handling data obsolescence over time. Drew outlines how enterprise platforms tier data storage dynamically based on time horizons.38:30–42:32 · Matt pushing back 3/10 Audience Q&A: Network Inventions and Ethics in Big Data An audience member proposes an unfocused question about a nation-scale GPS invention, prompting Matt to firmly step in and redirect the discussion offline. Drew then shares thoughts on big data ethics and privacy.

speaking balance: gold is Matt, purple is the guest (3 minute bins)

0:00 · Matt 41% · guest 59%0:00 · Matt 41% · guest 59%3:00 · Matt 4.9% · guest 95.1%3:00 · Matt 4.9% · guest 95.1%6:00 · Matt 8.3% · guest 91.7%6:00 · Matt 8.3% · guest 91.7%9:00 · Matt 14.5% · guest 85.5%9:00 · Matt 14.5% · guest 85.5%12:00 · Matt 14.4% · guest 85.6%12:00 · Matt 14.4% · guest 85.6%15:00 · Matt 8.3% · guest 91.7%15:00 · Matt 8.3% · guest 91.7%18:00 · Matt 6% · guest 94%18:00 · Matt 6% · guest 94%21:00 · Matt 0% · guest 100%21:00 · Matt 0% · guest 100%24:00 · Matt 2.2% · guest 97.8%24:00 · Matt 2.2% · guest 97.8%27:00 · Matt 0.2% · guest 99.8%27:00 · Matt 0.2% · guest 99.8%30:00 · Matt 0% · guest 100%30:00 · Matt 0% · guest 100%33:00 · Matt 0% · guest 100%33:00 · Matt 0% · guest 100%36:00 · Matt 0% · guest 100%36:00 · Matt 0% · guest 100%39:00 · Matt 6.2% · guest 93.8%39:00 · Matt 6.2% · guest 93.8%42:00 · Matt 26.9% · guest 73.1%42:00 · Matt 26.9% · guest 73.1%
Sharpest disagreement ▶ 33:55 Audience member challenges SQL relevance

An audience member forcefully asserts that no data scientists use SQL anymore and directly questions why anyone would choose MemSQL over MongoDB.

Hardest push from Matt ▶ 40:36 Matt cuts off off-topic question

Matt politely but firmly shuts down an unproductive and confusing audience query about satellite-free GPS, insisting it be taken offline.

Biggest teaching moment ▶ 35:14 Eric details technical flaws of MongoDB

Eric educates the audience on MongoDB's performance limitations, specifically contrasting its global write lock and schema repetition with MemSQL's concurrent relational engine.

Matt holds his own ▶ 10:35 Matt challenges premise on open-source software

When Drew suggests that difficult technical problems are open-sourced, Matt counters with domain knowledge by pointing out that databases are notoriously hard yet predominantly open-sourced.

the scores for every segment, with the reasoning behind each
ChapterTopicMatt as informed peerGuest teachingGuest disagreementMatt pushing backWhy
Panelist Origins and Company Evolution 1211 Matt opens the panel with lightweight origin questions about the founders' transitions into entrepreneurship. Oren playfully corrects Matt's narrative about VCs forcing Sqrrl to relocate to Boston.
MemSQL Stealth Development and In-Memory Architecture 1210 An audience member asks about MemSQL's stealth period, prompting Eric to explain the technical necessity of building an in-memory database from scratch. The host acts purely as a facilitator passing the microphone.
Open Source vs. Proprietary Database Models 3322 Matt prompts a debate on open-source versus proprietary models and interjects to note that complex database software is frequently open-sourced. Eric argues open source is a great marketing tool but a poor business model.
Database Paradigms: NoSQL vs. NewSQL 4422 Matt questions whether NoSQL and NewSQL vendors compete directly and asks about enterprise cloud adoption across industry verticals. The guests explain how relational models are evolving past NoSQL key-value limitations.
Audience Q&A: Security Policies and Unstructured Data 1210 Audience members inquire about enterprise security standards and unstructured data capabilities. Oren explains how fine-grained security policies can be embedded directly into database keys.
Audience Q&A: Data Locality and Enterprise Compliance 1321 Audience questions focus on memory locality and enterprise compliance. Oren uses a colorful analogy comparing specialized extreme performance tools to a Formula One car versus ten thousand versatile Kias.
Audience Q&A: Shared-Nothing Architecture and SQL vs. MongoDB 1430 Audience members challenge panelists on shared-nothing architectures, data marketplace value, and SQL versus MongoDB relevance. Eric details MongoDB's performance constraints, including its global write lock.
Audience Q&A: Data Obsolescence and Multi-Database Architectures 1310 An audience member asks about handling data obsolescence over time. Drew outlines how enterprise platforms tier data storage dynamically based on time horizons.
Audience Q&A: Network Inventions and Ethics in Big Data 2223 An audience member proposes an unfocused question about a nation-scale GPS invention, prompting Matt to firmly step in and redirect the discussion offline. Drew then shares thoughts on big data ethics and privacy.

Statements from this episode (18)

Disclosure
InfoChimps pivoted from data content marketplace to infrastructure platform
“We couldn't get enough revenue by just selling the content. But as soon as people found out, we pivoted to, hey, this platform we built to support our marketplace, you can have one of these.”
Drew (InfoChimps) Dec 5, 2013 ▶ 5:44
Disclosure
MemSQL raised millions post-YC and stayed stealth for 15 months
“We were able to raise a couple million following the program. We shut up shop in San Francisco and then basically went stealth for 1415 months. Launched the product just this year in June”
Eric (MemSQL) Dec 5, 2013 ▶ 7:28
Assertion Not checkable as stated
Eric Frenkiel claims building a database in 14 months is a record
“Doing it in 14 months is pretty much, I think, you know, a record.”
Eric Frenkiel Dec 5, 2013 ▶ 8:39
Disclosure
MemSQL founders entered Y Combinator with zero lines of code
“The funny thing is, is that we entered the program with zero lines of code.”
Eric Frenkiel Dec 5, 2013 ▶ 8:57
Assertion Contradicted
InfoChimps receives more external code commits than internal ones
“And we're getting more commits from folks outside the company now than we are from inside”
Drew (InfoChimps) Dec 5, 2013 ▶ 10:48
Opinion
MemSQL's Eric Frenkiel: Open source is a marketing channel, not business model
“I think open source is, is fantastic. It's a great marketing channel. I don't think it's a great business model.”
Eric (MemSQL) Dec 5, 2013 ▶ 10:57
What-if
Eric Frenkiel: MemSQL would not exist if launched as an open-source project
“Fundamentally I don't think MemSQL would exist if we had to go into it the open source way.”
Eric (MemSQL) Dec 5, 2013 ▶ 11:34
Prediction Not checkable as stated
Sqrrl's Oren Falkowitz predicts large enterprises will adopt polyglot database architectures
“So, I think for large enterprises, they'll probably want one of everything.”
Oren (Sqrrl) Dec 5, 2013 ▶ 13:24
Insight
MemSQL's Eric Frenkiel argues analytics cannot be performed in key-value stores
“I mean I think, I mean, it's, you can't do analytics in key value.”
Eric (MemSQL) Dec 5, 2013 ▶ 13:29
Prediction Not checkable as stated
Drew Bansal predicts enterprises will put sensitive data in cloud by 2022
“I can see a world in which 10 years from now those are also ok.”
Drew (InfoChimps) Dec 5, 2013 ▶ 15:16
Assertion Not checkable as stated
MemSQL's Eric Frenkiel argues on-premise infrastructure costs a fraction of AWS EC2
“I have a lot of you know, folks that spend tens of thousands of dollars a month on EC-II and they could do it for a fraction of the price if they did it on premise.”
Eric (MemSQL) Dec 5, 2013 ▶ 17:26
Assertion Partly supported
Frenkiel: MemSQL on EC2 achieves 1ms latency vs 60ms for MySQL
“Whenever you go with MM-SQL on EC-II, for example, you will see, like, one millisecond response times, and a Postgres or a MySQL is on the order of 60.”
Eric (MemSQL) Dec 5, 2013 ▶ 18:26
Insight
Eric Frenkiel: Writing a lightweight parser is easier than unstructured analysis
“What we typically see with unstructured data is it's far easier to write a lightweight parser around that log file, for example, and get it structured very readily.”
Eric (MemSQL) Dec 5, 2013 ▶ 20:49
Assertion Not checkable as stated
Frenkiel: Moving data from disk to memory yields a 50x speedup
“Just putting data from disk into memory, you'll see, you know, on the order of a 50 x improvement.”
Eric (MemSQL) Dec 5, 2013 ▶ 23:55
Insight
InfoChimps co-founder: Companies pay for internal data integration, not public data
“So I feel like data mashing together and shareability is hugely important, and it's something that folks are willing to pay for within an organization for internal data. Maybe not necessarily, at least in our company's experience, for data that is coming exter…”
Drew (InfoChimps) Dec 5, 2013 ▶ 32:09
Assertion Contradicted
Eric Frenkiel criticizes MongoDB for relying on a global write lock
“Mongo also has a global write lock. So one writer will block everyone else until it completes.”
Eric (MemSQL) Dec 5, 2013 ▶ 35:15
Prediction Not checkable as stated
InfoChimps' Drew Bansal: Personal privacy is going to die eventually
“I feel like privacy is going to die eventually, like it's going to be over, we can't stop it, it's already happened sort of thing”
Drew (InfoChimps) Dec 5, 2013 ▶ 41:37
Insight
Drew Bansal asserts open and transparent data limits potential data misuse
“I like that when data is open and transparent and easily shared and easily indexed and discovered, that you can limit a lot of the bad stuff that people can do with it”
Drew (InfoChimps) Dec 5, 2013 ▶ 42:07
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