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Aaron Morton
Robin Schumacher
                   1
• 40 minute webinar
• 15 minute Q+A
  • #CassandraQA
  • WebEx Q&A window
• Slides and recording will be available
• Next webcast:
  • Time for a new relationship?(Information Week)
  • September 26th


                                                     2
Aaron Morton (@aaronmorton)
DataStax MVP for Apache Cassandra
Aaron Morton is a Freelance Developer based in New Zealand, and a
Committer on the Apache Cassandra project. In 2010 he gave up the RDBMS
world for the scale and reliability of Cassandra. He now spends his time
advancing the Cassandra project and helping others get the best out of it.
www.thelastpickle.com




                                                                             3
Robin Schumacher
VP of Products @ DataStax
Robin Schumacher has spent the last 20 years working with databases and big data.
Before DataStax he was at EnterpriseDB, where he built and led a market-driven
product management group. Previously, Robin started and led the product
management team at MySQL for three years before they were bought by Sun, and
then by Oracle. He also started and led the product management team at
Embarcadero Technologies.
Robin is the author of three database performance books and frequent speaker at
industry events. Robin holds BS, MA, and Ph.D. degrees from various universities.




                                                                                4
5
6
7
8
First ANSI
1986
          standard.
1989    FOREIGN KEY
       New types, JOIN,
1992   DDL, Transaction
        Isolation Levels
1999       Triggers
                           9
First public
1996, v3.19
                  release

              MyISAM engine,
1999, v3.23
              no Transactions
              InnoDB, ACID
2001, v4.X     Transactions,
              FOREIGN KEY       10
PRIMARY KEY,
1995, v6.0
              FOREIGN KEY
1996, v6.5         JOIN
                NVARCHAR,
1998, v7.0
                 replication
                 Referential
2000, v2000
              Integrity actions
                                  11
Small limited
1989, v1.0
                  release
1997, v6.2        Triggers

1998, v6.3      Sub selects
                   MVCC
1999, v6.5.3
                Transactions
               FOREIGN KEY,
2000, v7.0.3
                   JOIN         12
• Adds application complexity
• Adds operational complexity
• Thundering Herds
• “There are 2 hard problems in computer science:
caching, naming, and off-by-1 errors”




                                               13
• Adds application complexity
  • Adds operational complexity
• Schema defined in multiple databases
• SPOF for shard
•Hard to grow and keep balanced




                                         14
• Fail over may add application complexity
• Unknown asynchronous delay in
    replication
• Potentially wasting resources on Slave
• Reliability of passive Slave is unknown
• “We failed to fail over to the slave.”




                                             15
• Adds application complexity
• Unknown asynchronous delay in replication
• SPOF for writes




                                              16
• ALTER TABLE locks the table
• Must be applied to many individual servers
• “foo varchar(50) DEFAULT NULL”




                                               17
18
19
20
21
2007   Tokyo Cabinet
2009   Redis
2009   Voldemort
2009   Riak




                       22
2008   Apache Couch DB
2009   MongoDB




                         23
2007   Neo4J
2009   Infogrid
2010   InfiniteGraph




                       24
Apache Hbase (as
   2007
              part of Lucene)
              BigTable as part of
2008 / 2011
              Google App Engine

   2009       Apache Cassandra

   2012       Amazon DynamoDB


                                    25
• Cluster based
• Replication built in
• No schema or flexible schema
• Expect node failure




                                 26
• Aaron Morton
 • @aaronmorton
 • www.thelastpickle.com




Licensed under a Creative Commons Attribution-NonCommercial 3.0 New Zealand License
                                                                                      27
Why NoSQL..?




               28
“NoSQL is the stuff of the Internet
Age.”
                             - Andrew Oliver,
                 InfoWorld




                                                29
What Characterizes the “Internet Age” with data?

1. Big Data – Concerns…
   • Scaling data velocity, variety, volume
2. Data in the Cloud – Promises…
   • Transparent elasticity
   • Scalability
   • Availability
   • Ease of use (data distribution, redundancy, etc.)
   • All these also needed on premise…
3. Data “everywhere” – needing to support multiple
   data centers, geographies, etc.


                                                    30
Why NoSQL?
You have Big Data use cases.
• Volume, variety, volume
• Complexity of data distribution
• Future proof apps where scaling is concerned



“Big data technologies describe a new
generation of technologies and
architectures, designed to economically
extract value from very large volumes of
a wide variety of data, by enabling high-
velocity capture, discovery, and/or
analysis ” - IDC




                                                 31
Why NoSQL?
Cassandra – a massively scalable NoSQL database
•     Superior write performance for data velocity
•     Strong data type support for data variety
•     Linear scalability/scale out for data volume
•     Fast for both reads and writes



    “We‟ve seen a 700% performance
    improvement, while our database grew over
    500% at the same time. Plus we‟ve saved
    40% in operational costs.” - SourceNinja




                                                     32
Why NoSQL? Cassandra and Performance
“In terms of scalability, there is a clear winner
throughout our experiments. Cassandra
achieves the highest throughput for the
maximum number of nodes in all experiments
with a linear increasing throughput.”
Solving Big Data Challenges for Enterprise Application Performance Management, Tilman Rable,
et al., August 2012, p. 10. Benchmark paper presented at the Very Large Database Conference,
2012. http://vldb.org/pvldb/vol5/p1724_tilmannrabl_vldb2012.pdf

                       In the Cloud…                                                 In Web Apps…




                                                                           YCSB Benchmark
                                                                           Source: http://blog.cubrid.org/dev-platform/nosql-
http://techblog.netflix.com/2011/11/benchmarking-cassandra-scalability-
                                                                           benchmarking/?utm_source=NoSQL+Weekly+List&utm_campaign=143fae8
on.html
                                                                           6b2-NoSQL_Weekly_Issue_41_September_8_2011&utm_medium=email
                                                                                                                                   33
Why NoSQL?
You need continuous availability.
• Different than high availability
• For applications that can’t go down
• May involve one or multiple locations




                                          34
Why NoSQL?
Cassandra – a continuously available NoSQL DBMS
• Built to overcome the fact that hardware failures can and do
  occur
• No single point of failure
• Out-of-the-box redundancy of function and data



“For us, the primary motivating factors are continuous
availability and multi-data center support. We also like
the fact that we can trust Cassandra; when we need to
write data, we don‟t have to worry that it‟s going to get
written and be there no matter what.”- RightScale




                                                            35
Why NoSQL?
You need true location independence.
• Need to read AND write data anywhere
• Data is eventually synchronized in all locations
• Keep data local for fast access




                                                     36
Why NoSQL?
Cassandra – a location independent database
•   Replication is multi-data center, multi-directional capable
•   Handles multiple cloud geo-zones
•   Supports hybrid on-premise/cloud deployments
•   Tunable data consistency



“I can create a Cassandra cluster in any region
of the world in 10 minutes. When marketing
decide we want to move into a certain part of
the world, we‟re ready.”- Netflix




                                                                  37
Why NoSQL?
You need real-time, transactional capabilities
• For applications needing ACID, use RDBMS
• For applications without ACID requirements, but with
  transactional needs, use NoSQL
• The “C” is ACID does not apply to NoSQL; the “C” in the CAP
  theorem does

“Ninety-five percent (95%) of database-driven
systems today don‟t need ACID transactions.”
– Dan McCreary, The CIO‟s Guide to NoSQL
Webinar




                                                          38
Why NoSQL?
Cassandra – real-time NoSQL transactions
• Supports AID transactions: atomic, isolated, and durable
• Provides tunable data consistency – per operation – to
  handle the “C” in the CAP theorem
• No ACID “C” as there are no referential integrity/foreign key
  constraints

“Cassandra stands at the front of the NoSQL
pack when it comes to supporting real-time,
Big Data applications.” – Wikibon




                                                              39
Why NoSQL?
You need a more flexible/agile data model.
• Escape the rigidity of the relational data model
• Able to easily store and access all data types
• Few worries about performance of “wide” rows




                                                     40
Why NoSQL?
The Cassandra Data Model - Bigtable
• A row-oriented, column structure
• A column family is similar to an RDBMS table but is
  more flexible/dynamic
• A row in a column family is indexed by its key.
  Other columns may be indexed as well

“Cassandra‟s NoSQL data model allows us       Keyspace
to insert and query data much more
naturally than what we had previously. The       Column Family
analysts who routinely use this data were
impressed with the flexibility and speed at       ID     Name    SSN   DOB

which the queries came back.” - NASA




                                                                             41
Why NoSQL?
You need a better architecture.
• Master/slave – inherent issues; write bottlenecks
• Sharding – difficult to setup/maintain
• Shared storage – has availability concerns




                                                      42
Why NoSQL?
Cassandra – a “masterless” architecture
•   Peer-to-peer design
•   No write bottlenecks
•   No manual sharding or shared storage issues
•   Less operational overhead



“Cassandra was just a better design all around
– more truly horizontally scalable and with less
management overhead – and there‟s no single
point of failure. I looked at Cassandra‟s
architecture and thought, „Yeah, that‟s how you
do it.‟” - Backupify




                                                   43
Why NoSQL?
Because you need…
•   The ability to handle big data use cases
•   Continuous availability vs. high availability
•   A location independent database
•   A real-time, transactional database
•   A more flexible/agile data model
•   A better architecture




                                                    44
Key Cassandra Use Cases
• Real-time, big data workloads
• Time series data management
• High-velocity device data consumption and analysis
• Media streaming management (e.g., music, movies)
• Social media (i.e., unstructured data) input and analysis
• Online web retail (e.g., shopping carts, user transactions)
• Real-time data analytics
• Online gaming (e.g., real-time messaging)
• Software as a Service (SaaS) applications that utilize web
  services
• Online portals (e.g. healthcare provider/patient interactions)
• Most write-intensive systems



                                                               45
Why NoSQL?




             - The CIO‟s Guide to NoSQL, Dan McCreary



                                                    46
• Cassandra.Apache.org
• PlanetCassandra.org
• Datastax.com




                         47

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DataStax C*ollege Credit: What and Why NoSQL?

  • 2. • 40 minute webinar • 15 minute Q+A • #CassandraQA • WebEx Q&A window • Slides and recording will be available • Next webcast: • Time for a new relationship?(Information Week) • September 26th 2
  • 3. Aaron Morton (@aaronmorton) DataStax MVP for Apache Cassandra Aaron Morton is a Freelance Developer based in New Zealand, and a Committer on the Apache Cassandra project. In 2010 he gave up the RDBMS world for the scale and reliability of Cassandra. He now spends his time advancing the Cassandra project and helping others get the best out of it. www.thelastpickle.com 3
  • 4. Robin Schumacher VP of Products @ DataStax Robin Schumacher has spent the last 20 years working with databases and big data. Before DataStax he was at EnterpriseDB, where he built and led a market-driven product management group. Previously, Robin started and led the product management team at MySQL for three years before they were bought by Sun, and then by Oracle. He also started and led the product management team at Embarcadero Technologies. Robin is the author of three database performance books and frequent speaker at industry events. Robin holds BS, MA, and Ph.D. degrees from various universities. 4
  • 5. 5
  • 6. 6
  • 7. 7
  • 8. 8
  • 9. First ANSI 1986 standard. 1989 FOREIGN KEY New types, JOIN, 1992 DDL, Transaction Isolation Levels 1999 Triggers 9
  • 10. First public 1996, v3.19 release MyISAM engine, 1999, v3.23 no Transactions InnoDB, ACID 2001, v4.X Transactions, FOREIGN KEY 10
  • 11. PRIMARY KEY, 1995, v6.0 FOREIGN KEY 1996, v6.5 JOIN NVARCHAR, 1998, v7.0 replication Referential 2000, v2000 Integrity actions 11
  • 12. Small limited 1989, v1.0 release 1997, v6.2 Triggers 1998, v6.3 Sub selects MVCC 1999, v6.5.3 Transactions FOREIGN KEY, 2000, v7.0.3 JOIN 12
  • 13. • Adds application complexity • Adds operational complexity • Thundering Herds • “There are 2 hard problems in computer science: caching, naming, and off-by-1 errors” 13
  • 14. • Adds application complexity • Adds operational complexity • Schema defined in multiple databases • SPOF for shard •Hard to grow and keep balanced 14
  • 15. • Fail over may add application complexity • Unknown asynchronous delay in replication • Potentially wasting resources on Slave • Reliability of passive Slave is unknown • “We failed to fail over to the slave.” 15
  • 16. • Adds application complexity • Unknown asynchronous delay in replication • SPOF for writes 16
  • 17. • ALTER TABLE locks the table • Must be applied to many individual servers • “foo varchar(50) DEFAULT NULL” 17
  • 18. 18
  • 19. 19
  • 20. 20
  • 21. 21
  • 22. 2007 Tokyo Cabinet 2009 Redis 2009 Voldemort 2009 Riak 22
  • 23. 2008 Apache Couch DB 2009 MongoDB 23
  • 24. 2007 Neo4J 2009 Infogrid 2010 InfiniteGraph 24
  • 25. Apache Hbase (as 2007 part of Lucene) BigTable as part of 2008 / 2011 Google App Engine 2009 Apache Cassandra 2012 Amazon DynamoDB 25
  • 26. • Cluster based • Replication built in • No schema or flexible schema • Expect node failure 26
  • 27. • Aaron Morton • @aaronmorton • www.thelastpickle.com Licensed under a Creative Commons Attribution-NonCommercial 3.0 New Zealand License 27
  • 29. “NoSQL is the stuff of the Internet Age.” - Andrew Oliver, InfoWorld 29
  • 30. What Characterizes the “Internet Age” with data? 1. Big Data – Concerns… • Scaling data velocity, variety, volume 2. Data in the Cloud – Promises… • Transparent elasticity • Scalability • Availability • Ease of use (data distribution, redundancy, etc.) • All these also needed on premise… 3. Data “everywhere” – needing to support multiple data centers, geographies, etc. 30
  • 31. Why NoSQL? You have Big Data use cases. • Volume, variety, volume • Complexity of data distribution • Future proof apps where scaling is concerned “Big data technologies describe a new generation of technologies and architectures, designed to economically extract value from very large volumes of a wide variety of data, by enabling high- velocity capture, discovery, and/or analysis ” - IDC 31
  • 32. Why NoSQL? Cassandra – a massively scalable NoSQL database • Superior write performance for data velocity • Strong data type support for data variety • Linear scalability/scale out for data volume • Fast for both reads and writes “We‟ve seen a 700% performance improvement, while our database grew over 500% at the same time. Plus we‟ve saved 40% in operational costs.” - SourceNinja 32
  • 33. Why NoSQL? Cassandra and Performance “In terms of scalability, there is a clear winner throughout our experiments. Cassandra achieves the highest throughput for the maximum number of nodes in all experiments with a linear increasing throughput.” Solving Big Data Challenges for Enterprise Application Performance Management, Tilman Rable, et al., August 2012, p. 10. Benchmark paper presented at the Very Large Database Conference, 2012. http://vldb.org/pvldb/vol5/p1724_tilmannrabl_vldb2012.pdf In the Cloud… In Web Apps… YCSB Benchmark Source: http://blog.cubrid.org/dev-platform/nosql- http://techblog.netflix.com/2011/11/benchmarking-cassandra-scalability- benchmarking/?utm_source=NoSQL+Weekly+List&utm_campaign=143fae8 on.html 6b2-NoSQL_Weekly_Issue_41_September_8_2011&utm_medium=email 33
  • 34. Why NoSQL? You need continuous availability. • Different than high availability • For applications that can’t go down • May involve one or multiple locations 34
  • 35. Why NoSQL? Cassandra – a continuously available NoSQL DBMS • Built to overcome the fact that hardware failures can and do occur • No single point of failure • Out-of-the-box redundancy of function and data “For us, the primary motivating factors are continuous availability and multi-data center support. We also like the fact that we can trust Cassandra; when we need to write data, we don‟t have to worry that it‟s going to get written and be there no matter what.”- RightScale 35
  • 36. Why NoSQL? You need true location independence. • Need to read AND write data anywhere • Data is eventually synchronized in all locations • Keep data local for fast access 36
  • 37. Why NoSQL? Cassandra – a location independent database • Replication is multi-data center, multi-directional capable • Handles multiple cloud geo-zones • Supports hybrid on-premise/cloud deployments • Tunable data consistency “I can create a Cassandra cluster in any region of the world in 10 minutes. When marketing decide we want to move into a certain part of the world, we‟re ready.”- Netflix 37
  • 38. Why NoSQL? You need real-time, transactional capabilities • For applications needing ACID, use RDBMS • For applications without ACID requirements, but with transactional needs, use NoSQL • The “C” is ACID does not apply to NoSQL; the “C” in the CAP theorem does “Ninety-five percent (95%) of database-driven systems today don‟t need ACID transactions.” – Dan McCreary, The CIO‟s Guide to NoSQL Webinar 38
  • 39. Why NoSQL? Cassandra – real-time NoSQL transactions • Supports AID transactions: atomic, isolated, and durable • Provides tunable data consistency – per operation – to handle the “C” in the CAP theorem • No ACID “C” as there are no referential integrity/foreign key constraints “Cassandra stands at the front of the NoSQL pack when it comes to supporting real-time, Big Data applications.” – Wikibon 39
  • 40. Why NoSQL? You need a more flexible/agile data model. • Escape the rigidity of the relational data model • Able to easily store and access all data types • Few worries about performance of “wide” rows 40
  • 41. Why NoSQL? The Cassandra Data Model - Bigtable • A row-oriented, column structure • A column family is similar to an RDBMS table but is more flexible/dynamic • A row in a column family is indexed by its key. Other columns may be indexed as well “Cassandra‟s NoSQL data model allows us Keyspace to insert and query data much more naturally than what we had previously. The Column Family analysts who routinely use this data were impressed with the flexibility and speed at ID Name SSN DOB which the queries came back.” - NASA 41
  • 42. Why NoSQL? You need a better architecture. • Master/slave – inherent issues; write bottlenecks • Sharding – difficult to setup/maintain • Shared storage – has availability concerns 42
  • 43. Why NoSQL? Cassandra – a “masterless” architecture • Peer-to-peer design • No write bottlenecks • No manual sharding or shared storage issues • Less operational overhead “Cassandra was just a better design all around – more truly horizontally scalable and with less management overhead – and there‟s no single point of failure. I looked at Cassandra‟s architecture and thought, „Yeah, that‟s how you do it.‟” - Backupify 43
  • 44. Why NoSQL? Because you need… • The ability to handle big data use cases • Continuous availability vs. high availability • A location independent database • A real-time, transactional database • A more flexible/agile data model • A better architecture 44
  • 45. Key Cassandra Use Cases • Real-time, big data workloads • Time series data management • High-velocity device data consumption and analysis • Media streaming management (e.g., music, movies) • Social media (i.e., unstructured data) input and analysis • Online web retail (e.g., shopping carts, user transactions) • Real-time data analytics • Online gaming (e.g., real-time messaging) • Software as a Service (SaaS) applications that utilize web services • Online portals (e.g. healthcare provider/patient interactions) • Most write-intensive systems 45
  • 46. Why NoSQL? - The CIO‟s Guide to NoSQL, Dan McCreary 46

Hinweis der Redaktion

  1. http://www.infoworld.com/d/data-management/the-time-nosql-standards-now-194998