The document argues that NoSQL technology takes a step back from relational databases by complicating data integration and quality assurance, and that NoSQL systems will eventually just become another feature of database management systems and cloud computing services, with future "PostSQL" databases being indistinguishable from general data communication services.

1. “For those of you who think we are engaged in
some sort of darwinian processes that make things
better for us, it’s actually quite the opposite.”
– Alan Kay, 2011
http://bit.ly/AlanKay2011

2. infinipool
NoSQL – Back to the Future
or Yet Another DB Feature?
A deconstruction of NoSQL – all carried out by an arrogant guy.

3. On Database History
and NoSQL
Martin Scholl, infinipool GmbH
martin@infinipool.com
@zeit_geist
Disclaimer:
What follows are opinion statements by an
otherwise unimportant guy. Pictures are
copyrighted by their respective owners.

4. On Database History
and NoSQL
Martin Scholl, infinipool GmbH
martin@infinipool.com
@zeit_geist
Studied all the different
*SQL-Systems out there.
Still having data issues.
Disclaimer: (Dr. Faustus)
What follows are opinion statements by an
otherwise unimportant guy. Pictures are
copyrighted by their respective owners.

5. On Database History
and NoSQL
I am the spirit that
Martin Scholl, infinipool GmbH
martin@infinipool.com
denies NoSQL.
(Mephisto. That’s me.)
@zeit_geist
Studied all the different
*SQL-Systems out there.
Still having data issues.
Disclaimer: (Dr. Faustus)
What follows are opinion statements by an
otherwise unimportant guy. Pictures are
copyrighted by their respective owners.

7. Arrogant guy
☞

8. Arrogant guy
☞
with a history book
☞

9. Arrogant guy
☞
with a history book
☞
...now making bold
statements
☞

10. Claim #1:
NoSQL Technology is a step back.

11. NoSQL Myth #1:
NoSQL Technology models Applications
more closely than traditional Databases.

13. Graph-
based Data
+ Counters

14. Graph-
based Data
+ Counters
Recommen-
dation Data

15. Graph-
based Data
+ Counters
Recommen-
dation Data
Journal-like
Data

16. “real-time”
Graph-
Data
based Data
+ Counters
Recommen-
dation Data
Journal-like
Data

17. infinipool
NoSQL vs Reality
• Data is scattered all over NoSQL land!
• No (simple) way to ensure various quality domains of data
• timeliness and appropriateness
• correctness and consistency
• Data Integration and Data Quality assurance becomes a full-stack concern!

18. NoSQL Myth #2:
There are no transactions in NoSQL
because transactions do not scale.

19. infinipool
Calvin: Fast Distributed Transactions for
Partitioned Database Systems[1]
[1] http://cs-www.cs.yale.edu/homes/dna/papers/calvin-sigmod12.pdf

20. infinipool
Calvin: Fast Distributed Transactions for
Partitioned Database Systems[1]
No Excuses!
[1] http://cs-www.cs.yale.edu/homes/dna/papers/calvin-sigmod12.pdf

21. NoSQL Myth #3:
NoSQL Data Stores are faster.

22. Yes, they are fast.
Except the other guys do their homework, too.

23. infinipool
MySQL Cluster 7.2 (preview)
• 30 node MySQL cluster
• sporting 19.5m update
transactions per second[1]
• yet, it’s Oracle and we all know
its a benchmark business.
[1] http://mikaelronstrom.blogspot.co.uk/2012/05/mysql-cluster-727-achieves-1bn-update.html

24. Claim #1:
NoSQL Technology is a step back.

25. (c) Lawrence Livermore National Laboratory
Good old Pre-SQL
Filesystems and Databases.
Times: The IBM 704

26. Pre-SQL Databases:
Files
• “Data is stored in files with
interface between programs and
files”
• Separation and Isolation: Every
program has its own files and
formats
• Duplication, Synchronization,
Consistency: Programs share
data. Data is not necessarily
synchronized or in a consistent
state.
• Weak Security, High
maintenance Costs
http://www.comphist.org/computing_history/new_page_9.htm

27. infinipool
Databases over Files
Databases over NoSQL DBs
(Cassandra, HBase,
Files (1960’s) Riak, etc.)
Every program has Every Data Store has
Separation &
its own files and its own APIs and
Isolation formats Data Models
Duplication, Programs share data. Content Transferred into
Data not necessarily Hadoop. Limited
Synchronization, consistent, synchronized consistency by data
Consistency, or consistent model
Security, Almost no security; Almost no security;
Maintenance manual data Specialized
Costs processes personnel required

28. Edgar Frank
‘Ted’ Codd
• Landmark Paper: “A Relational
Model of Data for Large Shared
Data Banks”
• Father of Relational Database
Management Systems
• Basically invented what Twitter
and FB run on
• Now a +$12B business
• we owe him more than an
applause.

29. infinipool
Relational Database Model: The Good Parts
• Key Insight: Separate Logical Data Model from Physical Data Storage
• Radical Simplification of Data Access
• A phenomenal tool was introduced: Joins
• great for “single data insert, multiple views of data”

30. infinipool
Relational Databases and NoSQL
Relational NoSQL DBs
(Cassandra, HBase,
Databases Riak, etc.)
Logical & Physical
Separated Complected
Data Model
Duplication, Normalization; Denormalization; Data
Synchronization, Constraints for Quality an Application-
improved data quality level Problem
Consistency,
Scalability Issues; Almost no security;
Downsides some DBMSs quite Specialized
expensive personnel required

31. 1964
It’s Mainframes all over
Software is not a product
Databases over Files

32. 1964 1980
It’s Mainframes all over It’s Minicomputers all over
Software is not a product Software becomes a product
Databases over Files Relational DBMS + SQL

33. 1964 1980 2012
It’s Mainframes all over It’s Minicomputers all over
Software is not a product Software becomes a product
Databases over Files Relational DBMS + SQL

34. 1964 1980 2012
It’s Mainframes all over It’s Minicomputers all over It’s Cloud Computing all over
Software is not a product Software becomes a product Software becomes a Service
Databases over Files Relational DBMS + SQL

35. 1964 1980 2012
It’s Mainframes all over It’s Minicomputers all over It’s Cloud Computing all over
Software is not a product Software becomes a product Software becomes a Service
Databases over Files Relational DBMS + SQL NoSQL?

36. 1964 1980 2012
It’s Mainframes all over It’s Minicomputers all over It’s Cloud Computing all over
Software is not a product Software becomes a product Software becomes a Service
Databases over Files Relational DBMS + SQL NoSQL?
So far:
Every HW iteration a new DB Technology
Is Cloud Computing a backlash?
Will NoSQL prevail?

37. infinipool
Changing Issues in Data Management
• Scalability of data storage and transactional access is solved.
Everybody can (soon) rent the perfect data storage system in the cloud.
• Issue #1: Data-Integration an open task
• Issue #2: Data-Quality an open task
• Issue #3: Push-based execution model: where are thou?

38. infinipool
Changing Issues in Data Management
• Scalability of data storage and transactional access is solved.
Everybody can rent the perfect data storage system in the cloud.
• Issue #1: Data-Integration an open task
• Issue #2: Data-Quality an open task
• Issue #3: Push-based execution model: where are thou?
• The new competitive frontier: Timeliness, Data Integration and Quality

39. Claim #1:
NoSQL Technology is a step back.

40. Claim #1:
NoSQL Technology is a step back.
Claim #2:
NoSQL will become yet another DB Feature
and/or Cloud Computing Service.

41. Claim #1:
NoSQL Technology is a step back.
Claim #2:
NoSQL will become yet another DB Feature
and/or Cloud Computing Service.
Claim #3:
PostSQL Databases will be indistinguishable
from Data Communication Services.

42. infinipool
Thank you.
Martin Scholl, infinipool GmbH
martin@infinipool.com
@zeit_geist

43. Claim #1:
NoSQL Technology is a step back.
Claim #2:
NoSQL will become yet another DB Feature
and/or Cloud Computing Service.
Claim #3:
PostSQL Databases will be indistinguishable
from Data Communication Services.