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NoSQL like there is NoTomorrow 
Khawaja 
Engineering Lead for NoSQL, AWS 
@swami_79 @ksshams
NASA JPL has visited every planet in the 
@ksshams 
solar system ... except Pluto
25 Gbps!
NoSQL like there is No Tomorrow
NoSQL like there is No Tomorrow
NoSQL like there is No Tomorrow
@ksshams
let’s start with a trilogy … 
@swami_79 @ksshams
episode 1 
once upon a time... 
(in 2000) 
@swami_79 @ksshams
a half mile away... 
(Seattle) 
@swami_79 @ksshams
amazon.com - a rapidly growing Internet based 
retail business relied on relational databases 
@swami_79 @ksshams
we had 1000s of independent services 
@swami_79 @ksshams
each service managed its own state in 
Relational Databases 
@swami_79 @ksshams
Relational Databases 
are pretty seductive 
@swami_79 @ksshams
first of all... SQL!! 
@swami_79 @ksshams
so it is easier to query.. 
@swami_79 @ksshams
easier to learn 
@swami_79 @ksshams
They are as versatile as a swiss army knife 
key-value access complex queries 
analytics transactions 
@swami_79 @ksshams
Relational Databases 
are very similar to 
Swiss Army Knives 
@swami_79 @ksshams
sometimes.. swiss army knifes.. 
can be more than what you bargained for 
@swami_79 @ksshams
partitioning 
easy 
re-partitioning 
HARD.. 
@swami_79 @ksshams
so we bought 
bigger boxes... 
@swami_79 @ksshams
benchmark 
new hardware 
migrate to new 
hardware 
Q4 was hard-work at Amazon 
repartition 
databases 
pray 
... 
@swami_79 @ksshams
Relational Databases 
have availability challenges.. 
@swami_79 @ksshams
episode 2 
then.. (in 2005) 
@swami_79 @ksshams
amazon dynamo 
predecessor to dynamoDB 
replicated DHT with consistent hashing 
optimistic replication 
“sloppy quorum” 
anti-entropy mechanism 
object versioning 
specialist tool : 
•limited querying capabilities 
•simpler consistency 
@swami_79 @ksshams
dynamo had many benefits 
• higher availability 
• we traded it off for consistency 
• incremental scalability 
• no more repartitioning 
• no need to architect apps for peak 
• just add boxes 
• simpler querying model ==>> predictable performance 
@swami_79 @ksshams
but dynamo was not perfect... 
lacked strong consistency 
@swami_79 @ksshams
but dynamo was not perfect... 
scaling was easier, but... 
@swami_79 @ksshams
but dynamo was not perfect... 
steep learning curve 
@swami_79 @ksshams
but dynamo was not perfect... 
dynamo was a library ==>> not a service... 
@swami_79 @ksshams
episode 3 
then.. (in 2012) 
@swami_79 @ksshams
Managed NoSQL Database 
ADMIN 
DynamoDB 
Built for Scale 
Fast & Predictable Performance 
@swami_79 @ksshams
DynamoDB 
“Even though we have years of experience with large, 
complex NoSQL architectures, we are happy to be finally 
out of the business of managing it ourselves.” - Don 
MacAskill, CEO 
@swami_79 @ksshams
DynamoDB Goals and Philosophies 
durability and availability 
scale is our problem 
easy to use 
scale in rps 
consistent and low latencies 
@swami_79 @ksshams
durability is key… 
@swami_79 @ksshams
availability is key… 
@swami_79 @ksshams
scale is our problem, not yours.. 
@swami_79 @ksshams
Fault Tolerant Design 
Infrastructure Fails - deal with it! 
Planning for failures is not easy 
How do you ensure your recovery strategies work correctly? 
@swami_79 @ksshams
Byzantine General Problem 
@swami_79 @ksshams
A simple 2-way replication system of a traditional database… 
Writes 
@swami_79 @ksshams
S is dead, 
need to trigger 
new replica 
P is dead, need to 
promote myself 
P S 
@swami_79 @ksshams
Improved Replication: Quorum 
Writes 
Quorum: Successful write on a majority 
@swami_79 @ksshams
Easy? 
Writes from 
client X 
Reads and 
Writes from 
client Y 
Classic Split Brain Issue in Replicated systems leading to lost writes! 
@swami_79 @ksshams
Building correct distributed systems is not straight forward.. 
Handle replica failures 
Handle partial failures of replicas 
Handle concurrent failures 
Ensure there isn’t a parallel quorum 
@swami_79 @ksshams
Trends in the World Of Databases 
@swami_79 @ksshams
A decade ago, it was all about the DBAs 
@swami_79 @ksshams
Last 5 years have been about self service. 
@swami_79 @ksshams
Today is about managed services. 
@swami_79 @ksshams
Plan for Success … Plan for Scale 
@swami_79 @ksshams
@swami_79 @ksshams
@swami_79 @ksshams

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NoSQL like there is No Tomorrow

Editor's Notes

  1. This story will be a little biased because Swami and I are from the NoSQL generation and we really don’t like relational databases
  2. http://centerfordentalimplants.info/wp-content/uploads/2012/10/young-woman-holding-cheeks-in-surprise.jpg
  3. more people already know it, etc
  4. http://www.toolstop.co.uk/components/com_virtuemart/shop_image/product/399926c941f80748cd41a85a57f8c163.jpg
  5. http://www.toolstop.co.uk/components/com_virtuemart/shop_image/product/399926c941f80748cd41a85a57f8c163.jpg Swami
  6. http://www.swissknifeshop.com/media/catalog/product/cache/1/image/5e06319eda06f020e43594a9c230972d/W/G/WG16999.jpg They seriously don’t scale well and if you’re not careful and try to use all the features at once, you can get cut in the process
  7. it was like playing minesweeper
  8. RDBMs focus way too much on consistency - and compromise availability And seriously - are they really all that consistent? ever had slaves fall behind? or how about a recent bug we had where all slaves got updates, but the master didn’t take the update Like Swiss army knives - there is waaaay too much functionality in the knives. Let’s move it to the app (easier to debug and change). Developers often use transactions when they shouldn’t - very annoying - it is like bringing a swiss army knife through a TSA checkpoint. Just foolish
  9. Khawaja
  10. Swami:
  11. K:
  12. required action from developers Q4 scaling: While not as scary as phase 1, still was work Need benchmarking, patching, adding hardware, rebalancing clusters..
  13. developers still had to learn to set it up if you are building a recommendation system, you want to be learning k-clustering and collaborative filtering algorithms rather than focusing on lamport’s papers
  14. Swami: like s3 - and it required developers to be admins. this is the really key point - our developers wanted a service, not a product. If you look at mongodb, that is what they are doing today.
  15. K
  16. </K>
  17. 2 dc writes on disk continuous replication we should brag about availability
  18. multi-region service! Regional service spans multiple availability zones All data is continuously replicated to multiple AZ’s
  19. plan for success, plan for scalability