when more is less: evaluating new database technology in 2016, david rolfe, voltdb

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Page 1: When more is less: Evaluating new database technology in 2016, David Rolfe, VoltDB

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WHEN MORE IS LESS: EVALUATING NEW DATABASE TECHNOLOGY IN 2016. 

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Page 2: When more is less: Evaluating new database technology in 2016, David Rolfe, VoltDB

page 2© 2016 VoltDB PROPRIETARY page

•Tube map

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page 3© 2016 VoltDB PROPRIETARY

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page 5© 2016 VoltDB PROPRIETARY

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page 6© 2016 VoltDB PROPRIETARY

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http://i2.cdn.turner.com/money/2011/08/17/technology/military_energy/fuel-convoy.gi.top.jpg

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TRY TO DO EVERYTHING AND YOU’LL DO NOTHING WELL…• The more ‘stuff’ you add the less likely it is that you

can do everything properly.

• Over time legacy products ended up full of features that you pay for but don’t need.

• To add insult to injury the vendor will charge you more because it has more features

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A ”FEATURE MATRIX” FOR EVALUATING HADOOPFeature “BloatCorp* Distributed FS” HDFS

Hardware Acceleration Support for updates Simultaneous updates Support for small block sizes Replication

Conclusion: Hadoop is a great example of how Feature Matrices are no longer relevant and can be highly misleading when it comes to choosing technology

*“BloatCorp” is fictional

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WHY NOSQL/NEWSQL HAPPENED…• Existing products struggled with emerging needs:

• The Cloud / Virtualization• Commodity Hardware • New Use Cases• Cloud Economics• Distribution of data between multiple locations as standard• High Availability as standard• JSON, XML, CLOB, BLOB, Log files, >10KTPS OLTP……..

• Critically: A new generation of developers who couldn’t remember life before the RDBMS were unafraid to live without one.

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page 11© 2016 VoltDB PROPRIETARY page

•Tube map

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THE 2017 DILEMMA...• Every possible architecture is now available.• Everyone is claiming 10 to 100x faster.• We’ve gone from a chronic shortage of choice

to a glut….

• How do you pick the right database?

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page 13© 2016 VoltDB PROPRIETARY

COLIN CHAPMAN, THE MAN BEHIND LOTUS CARS

“Simplify, then add lightness”

“Adding power makes you faster on the straights; subtracting weight makes you faster everywhere”

When it comes to databases “speed” is a consequence of architectural choices, not clever programming….

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THE “FEATURE MATRIX” IS DEAD, BUT..• It’s easier to be 100x faster when you do

virtually nothing…

• Unneeded features == slowness, cost, complexity

• Missing features == problem doesn’t get solved

• Instead of one product that does everything you need a ‘Zoo’ of technologies.

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WHY THE “ZOO” ANALOGY?• Nobody will pay to go to an ”All giraffe zoo”• “Zoo” implies a balanced, rational collection..

• Nobody thinks Zoo animals look after themselves• Open source stops being free when you start

using it..

• A Zoo is not an animal shelter• Not in the business of offering homes to stray

technologies found on the internet…

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DATABASE TECHNOLOGY SELECTION CHECKLIST

1. Do we understand all the requirements?• We mean next year’s, not the next agile

iteration.• A database is for life, not just for

Christmas!• Need to distinguish between ‘need’ and

‘want’.• ‘want’ leads to feature bloat…

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DATABASE TECHNOLOGY SELECTION CHECKLIST

2. How will this fit into our Ecosystem?• “Ecosystem” includes people, skills,

culture...• Depending on your business customer’s

opinions may matter too…• Try and avoid overlap – having an Indian

and an African elephant wastes resources.

• Overlap also leads to office politics

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DATABASE TECHNOLOGY SELECTION CHECKLIST

3. What is the TCO?• Making decisions without regard to

economics means you’ll end up trying to use a Rolls Royce as an Ice Cream van.

• TCO includes zookeepers, cages, vets. Or trained staff, hardware and support contracts.

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DATABASE TECHNOLOGY SELECTION CHECKLIST

4. Will your chosen DB exist five years from now?• The ”Tube Map” is unsustainable in its current form.• An industry shakeout is unavoidable.• Deciding to support a dying Open Source platform

has serious TCO implications.• Cynical view: Platform survivability is the issue you

can’t get wrong.

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CONCLUSIONKnow what you need.• Do your own research.• Be wary of ‘extra’ features/bloat.• Ask “Is this the first DB these people have

written?”• Find out why architectural choices were made. Do

the reasons make sense to you?• Understand why it’s fast – something was left

out….• Think 5 years ahead. Make sure your vendor does.

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WHO IS VOLTDB?

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DAVID ROLFEDIRECTOR OF SOLUTIONS ENGINEERING, EMEA

[email protected]@SR_MAD_SCIENCEWWW.VOLTDB.COM

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THE VOLTDB TECHNOLOGY ORIGIN

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BIG DATA

Non Relational Processing

BI Reporting

Fast Operational

Database

FAST DATA

Export

Ingestion

Engine

Request &

Response

Application

Streaming

Analytics

Data Warehou

se Columnar Analytics

OLAP

DATA ARCHITECTURE FOR FAST + BIG DATA

Data Lake

(HDFS)

OUTSIDE WORLD

In Memory

Data

Real Time Data

Sources

End user or Device