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Morning with MongoDB Paris 2012 - Making Big Data Small
1. Making Big Data
Small:
Big Data for the Rest of Us
November 2012
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2. …2000
•Google announced it had released the largest
search engine on the Internet
•Google’s new index comprised more than 1 billion
URLs
•BIG!!!
2
3. …2008
•Our indexing system for processing links indicates
that we now count 1 trillion unique URLs
(and the number of individual web pages out there
is growing by several billion pages per day)
•BIGGER!!!!
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7. • Applies to more than just CPUs
• Summary version? Things double at regular
intervals
• It’s exponential growth…and applies to Big Data
BBC: “Your current PC is more powerful than the
computer they had on board the first flight to the
moon.”
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17. • In 1998 Google won the search race through
custom software and infrastructure
• In 2002 Amazon again wrote custom and
proprietary software to handle their BIG Data
needs
• In 2006 Facebook started with off the shelf
software, but quickly turned to developing their
own custom-built solutions
What do these have in common? Big Data was
critical to making them win
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25. Agile Development
• Iterative & continuous
• New and emerging
apps
Volume and Type
of Data
• Trillions of records
• 10’s of millions of New Architectures
queries per second • Systems scaling horizontally,
• Volume of data not vertically
• Semi-structured and • Commodity servers
unstructured data • Cloud Computing
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31. “Relational databases…[don’t] necessarily match the way we see our
data. mongoDB gave us the flexibility to store data in the way that
we understand it as opposed to somebody’s theoretical view.”
“It’s friendly. By friendly, I mean that coming from a relational
background, specifically a MySQL background, a lot of the concepts
carry over.... It makes it very easy to get started.”
“Selecting MongoDB as our database platform was a no brainer as the
technology offered us the flexibility and scalability that we knew
we’d need for Priority Moments.”
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