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SQL vs NoSQL THE NOSQL WAY
NoSQL MongoDBISN’T JUST
{“id” : …, “…” : …}
FILLING A NICHE WHY SO MANY?
SIMPLE DATA STORAGE CACHE SYSTEM CONFIGURATION MEMCACHED REDIS ZOOKEEPER ETCD
Etcd demo
DOCUMENT STORAGE MONGO COUCH DYNAMO
GRAPH DATA SOCIAL GRAPHS ROUTE DATA NEO4J
RELATIONAL LIKE BIG TABLE CLONES COLUMN FAMILY CASSANDRA
Cassandra demo
TIME SERIES DATA TIME SERIES DATABASES SPARSE COLUMN STORES INFLUX CASSANDRA
InfluxDB demo
THE NO IN NoSQL STANDS FOR NOT ONLY
WHEN SHOULD I USE NOSQL?
FREQUENTLY CHANGING MODEL LARGE SCALE SPECIAL USE CASE
WHAT DO I MEAN BY SCALE? SCALE UP SCALE OUT
JUST ENOUGH DISTRIBUTED SYSTEMS THEORY
CAP THEORY CONSISTENCY AVAILABILITY PARTITION TOLERANCE * NOT REALLY ANYMORE PICK TWO*
CA’S NOT POSSIBLE
BASIC AVAILABILITY, SOFT STATE, EVENTUAL CONSISTENCY VS ATOMIC CONSISTENT, ISOLATED, DURABLE
ACID IS POSSIBLE IN NOSQL
I’VE PICKED MY DATABASE, NOW WHAT?
SHIP IT BUT… KNOW THE RISKS DISTRIBUTED SYSTEMS AREN’T EASY CLOUD MAKES IT HARDER STILL
JEPSEN HTTP://APHYR.COM/TAGS/JEPSEN
IN CONCLUSION ENSURE YOUR USE CASE IS RIGHT KNOW THE RISKS PREPARE FOR FAILURE
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SQL vs NoSQL: The NoSQL way

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Slides from a showdown with Tony Rogerson in Southampton at DevSouthCoast talking about the NoSQL alternatives for data storage

Published in: Data & Analytics
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SQL vs NoSQL: The NoSQL way

  1. 1. SQL vs NoSQL THE NOSQL WAY
  2. 2. NoSQL MongoDBISN’T JUST
  3. 3. {“id” : …, “…” : …}
  4. 4. FILLING A NICHE WHY SO MANY?
  5. 5. SIMPLE DATA STORAGE CACHE SYSTEM CONFIGURATION MEMCACHED REDIS ZOOKEEPER ETCD
  6. 6. Etcd demo
  7. 7. DOCUMENT STORAGE MONGO COUCH DYNAMO
  8. 8. GRAPH DATA SOCIAL GRAPHS ROUTE DATA NEO4J
  9. 9. RELATIONAL LIKE BIG TABLE CLONES COLUMN FAMILY CASSANDRA
  10. 10. Cassandra demo
  11. 11. TIME SERIES DATA TIME SERIES DATABASES SPARSE COLUMN STORES INFLUX CASSANDRA
  12. 12. InfluxDB demo
  13. 13. THE NO IN NoSQL STANDS FOR NOT ONLY
  14. 14. WHEN SHOULD I USE NOSQL?
  15. 15. FREQUENTLY CHANGING MODEL LARGE SCALE SPECIAL USE CASE
  16. 16. WHAT DO I MEAN BY SCALE? SCALE UP SCALE OUT
  17. 17. JUST ENOUGH DISTRIBUTED SYSTEMS THEORY
  18. 18. CAP THEORY CONSISTENCY AVAILABILITY PARTITION TOLERANCE * NOT REALLY ANYMORE PICK TWO*
  19. 19. CA’S NOT POSSIBLE
  20. 20. BASIC AVAILABILITY, SOFT STATE, EVENTUAL CONSISTENCY VS ATOMIC CONSISTENT, ISOLATED, DURABLE
  21. 21. ACID IS POSSIBLE IN NOSQL
  22. 22. I’VE PICKED MY DATABASE, NOW WHAT?
  23. 23. SHIP IT BUT… KNOW THE RISKS DISTRIBUTED SYSTEMS AREN’T EASY CLOUD MAKES IT HARDER STILL
  24. 24. JEPSEN HTTP://APHYR.COM/TAGS/JEPSEN
  25. 25. IN CONCLUSION ENSURE YOUR USE CASE IS RIGHT KNOW THE RISKS PREPARE FOR FAILURE

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