DataStax: The Whys of NoSQL

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As the {no,new,not only} SQL market cements itself as a backbone for today's Internet Enterprise applications, it behoves us both as technologists and enterprise leaders, to understand "whys" of design choices of NoSQL systems. This talk will reflect upon the rationale of design choices within traditional RDBMS systems (e.g. 3NF, joins, transactions) and contrast them with the similar foundational concepts within NoSQL systems such as Cassandra.

Technologie

1 Jargon Galore
2 Schema
3 Modeling and Internals
4 Deployment
5 Conclusion
2© 2015. All Rights Reserved.

©2015 DataStax Conﬁdential. Do not distribute without consent.
3
SQL Jargon

©2015 DataStax Conﬁdential. Do not distribute without consent.
4
NoSQL Noise?

Schema
©2015 DataStax Conﬁdential. Do not distribute without consent.
Rigid
Schema
Schema
Free
Schema
on read
Schema
Easy to change
In flexible Writes are schema free,
reads are freaking slow
Reads/Writes are schema aware
Schema changes are O(1) operations
BLOBs
Too Slow
Optimized for Agility of change when needed, not theoretical extremes

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6
Normalization, Joins, Referential Integrity
Database normalization is the process of
organizing the columns (attributes) and
tables (relations) of a relational database
to minimize data redundancy.
Referential integrity is a property of data
which, when satisfied, requires every
value of one column of a table to exist
as a value of another column in a
different table.A JOIN is a means for combining
fields from two tables (or more) by
using values common to each.
Source - https://en.wikipedia.org/

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7
Not all Data Access is equal
1:168K random vs.
sequential
1:10 random vs.
sequential
Source - https://queue.acm.org/detail.cfm?id=1563874

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8
Disk Density
Source http://silvertonconsulting.com/blog/2010/04/22/save-the-planet-buy-fatter-disks-and-flash/#sthash.sh2nwqtX.dpbs

©2015 DataStax Conﬁdential. Do not distribute without consent.
9
$0.01
$0.10
$1.00
$10.00
$100.00
$1,000.00
$10,000.00
$100,000.00
$1,000,000.00
201420132010200520001995199019851980
HDD Price / GB
Minimize Data
Redundancy?
Disk Price / GB

OS Cache
C* Read and Write paths
©2015 DataStax Conﬁdential. Do not distribute without consent.
Memtable 1 Memtable 2 Memtable N
SSTable 1 SSTable 2 SSTable N
Commit Log
Persistent
Storage
Off Heap
In Process Memory
Reads (memtable + N SSTables where N >= 1)
Mandatory Flush
Writes
Max # of SSTables = N
(based on compaction)
Creation of new memtable during flush operation (cleanup
tombstones, cleanup token ranges, etc.)
Time (memtable_flush_in_ms controls the frequency)
Accounting
SSTable
Compacted
RANDOM ACCESS
SEQUENTIAL ACCESS

Execution Engine
©2015 DataStax Conﬁdential. Do not distribute without consent.

Key takeaways
©2015 DataStax Conﬁdential. Do not distribute without consent.
Optimal utilization of physical resources (random
access, sequential IO and CPU)
No Read before Write (well mostly!)
Plan for Compaction (like commercial paper, you need
a regular pay back)
De-Normalize for optimal application response (use
2NF instead of 3NF)

Deployment Semantics
©2014 DataStax Confidential. Do not distribute without consent.
R/W R
Single BoxDR
GR
ScaleUpby.
Sharding
Replication
GR + DR
San
Francisco
New York
Stockholm
DC1 DC2

Linear Scaling
©2015 DataStax Conﬁdential. Do not distribute without consent.
http://www.datastax.com/apache-cassandra-leads-nosql-benchmark
End Point Report Excerpt: Balanced Read/Write YCSB Test

So what's the catch?
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©2015 DataStax Conﬁdential. Do not distribute without consent.
16
Conclusion
Best in class performance, backed by physics

Enables pragmatic business agility,

Delivering delightful customer experience,

Always on, Linear Scale architecture delivering optimal ROI

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DataStax: The Whys of NoSQL

1. The Whys of NoSQL

5. Schema ©2015 DataStax Conﬁdential. Do not distribute without consent. Rigid Schema Schema Free Schema on read Schema Easy to change In flexible Writes are schema free, reads are freaking slow Reads/Writes are schema aware Schema changes are O(1) operations BLOBs Too Slow Optimized for Agility of change when needed, not theoretical extremes

6. ©2015 DataStax Conﬁdential. Do not distribute without consent. 6 Normalization, Joins, Referential Integrity Database normalization is the process of organizing the columns (attributes) and tables (relations) of a relational database to minimize data redundancy. Referential integrity is a property of data which, when satisfied, requires every value of one column of a table to exist as a value of another column in a different table.A JOIN is a means for combining fields from two tables (or more) by using values common to each. Source - https://en.wikipedia.org/

7. ©2015 DataStax Conﬁdential. Do not distribute without consent. 7 Not all Data Access is equal 1:168K random vs. sequential 1:10 random vs. sequential Source - https://queue.acm.org/detail.cfm?id=1563874

9. ©2015 DataStax Conﬁdential. Do not distribute without consent. 9 $0.01 $0.10 $1.00 $10.00 $100.00 $1,000.00 $10,000.00 $100,000.00 $1,000,000.00 201420132010200520001995199019851980 HDD Price / GB Minimize Data Redundancy? Disk Price / GB

10. OS Cache C* Read and Write paths ©2015 DataStax Conﬁdential. Do not distribute without consent. Memtable 1 Memtable 2 Memtable N SSTable 1 SSTable 2 SSTable N Commit Log Persistent Storage Off Heap In Process Memory Reads (memtable + N SSTables where N >= 1) Mandatory Flush Writes Max # of SSTables = N (based on compaction) Creation of new memtable during flush operation (cleanup tombstones, cleanup token ranges, etc.) Time (memtable_flush_in_ms controls the frequency) Accounting SSTable Compacted RANDOM ACCESS SEQUENTIAL ACCESS

12. Key takeaways ©2015 DataStax Conﬁdential. Do not distribute without consent. Optimal utilization of physical resources (random access, sequential IO and CPU) No Read before Write (well mostly!) Plan for Compaction (like commercial paper, you need a regular pay back) De-Normalize for optimal application response (use 2NF instead of 3NF)

16. ©2015 DataStax Conﬁdential. Do not distribute without consent. 16 Conclusion Best in class performance, backed by physics Enables pragmatic business agility, Delivering delightful customer experience, Always on, Linear Scale architecture delivering optimal ROI

17. Thank you

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