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TZID:America/Phoenix
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DESCRIPTION:<p>Amazon DynamoDB is a (popular) nonrelational database (NoSQ
 L) that delivers reliable performance at any scale. It's a fully managed 
 on AWS\, multi-region\, multi-master database that provides consistent si
 ngle-digit millisecond latency\, and offers built-in security\, backup an
 d restore\, and in-memory caching.</p>\n<p>To use DynamoDB effectively\, 
 one must understand key concepts like partition/hash keys or range/sort k
 eys to store NoSQL data\, scan vs query calls to access data\, projection
 s and expressions\, a mapper class for ORM\, global secondary indexing to
  allow adhoc querying\, asynchronous calls and batch read/write operation
 s.</p>\n<p>As a cloud offering\, Dynamo DB needs resource provisioning\, 
 time to live and autoscale configuration aligned with your application's 
 needs along with monitoring via Cloudwatch or 3rd party tools. In additio
 n\, Dynamo DB also provides in memory acceleration caching via DAX\, trig
 ger mechanism and data exports via data pipeline.</p>\n<p>This session wi
 ll cover how to effectively program for DynamoDB noSQL through judicious 
 choice of:</p>\n<ul>\n<li style="padding-left: 30px\;">Table data's prima
 ry keys\, secondary indices\, schema</li>\n<li style="padding-left: 30px\
 ;">In-memory caching (DAX)\, ORM Mapper class</li>\n<li style="padding-le
 ft: 30px\;">Effective and efficient ways of querying\, scanning (Query ex
 pression\, projections)</li>\n<li style="padding-left: 30px\;">Provisioni
 ng\, scaling and monitoring (Cloudwatch\, autoscale)</li>\n<li style="pad
 ding-left: 30px\;">Backups\, exports\, data pipeline for offline/realtime
  analytics</li>\n<li style="padding-left: 30px\;">Cost implications &amp\
 ; comparison (Using 2018 AWS $ rates in popular AWS region)</li>\n</ul>\n
 <p>Examples will be provided in Java\, Javascript/NodeJS and will walk th
 rough the AWS DynamoDB SDK and console with examples for table creation\,
  CRUD operations\, capacity management\, accelerator cache cluster config
  and security group settings.</p>\n<p>&nbsp\;</p>\n<pre>Keywords: Cloud\,
  NoSQL\, Dynamo\, AWS\, DAX\, Amazon\, Web Services\, Storage\, Database\
 , DynamoDB&nbsp\;</pre>
DTEND;TZID=America/Phoenix:20181006T163000
DTSTAMP:20260608T174630Z
DTSTART;TZID=America/Phoenix:20181006T153000
GEO:33.293070;-111.796620
LOCATION:Chandler - Gilbert Community College - IRN-227
ORGANIZER:
SEQUENCE:0
STATUS:CONFIRMED
SUMMARY:<p>Amazon DynamoDB is a (popular) nonrelational database (NoSQL) t
 hat delivers reliable performance at any scale. It's a fully managed on A
 WS\, multi-region\, multi-master database that provides consistent single
 -digit millisecond latency\, and offers built-in security\, backup and re
 store\, and in-memory caching.</p>\n<p>To use DynamoDB effectively\, one 
 must understand key concepts like partition/hash keys or range/sort keys 
 to store NoSQL data\, scan vs query calls to access data\, projections an
 d expressions\, a mapper class for ORM\, global secondary indexing to all
 ow adhoc querying\, asynchronous calls and batch read/write operations.</
 p>\n<p>As a cloud offering\, Dynamo DB needs resource provisioning\, time
  to live and autoscale configuration aligned with your application's need
 s along with monitoring via Cloudwatch or 3rd party tools. In addition\, 
 Dynamo DB also provides in memory acceleration caching via DAX\, trigger 
 mechanism and data exports via data pipeline.</p>\n<p>This session will c
 over how to effectively program for DynamoDB noSQL through judicious choi
 ce of:</p>\n<ul>\n<li style="padding-left: 30px\;">Table data's primary k
 eys\, secondary indices\, schema</li>\n<li style="padding-left: 30px\;">I
 n-memory caching (DAX)\, ORM Mapper class</li>\n<li style="padding-left: 
 30px\;">Effective and efficient ways of querying\, scanning (Query expres
 sion\, projections)</li>\n<li style="padding-left: 30px\;">Provisioning\,
  scaling and monitoring (Cloudwatch\, autoscale)</li>\n<li style="padding
 -left: 30px\;">Backups\, exports\, data pipeline for offline/realtime ana
 lytics</li>\n<li style="padding-left: 30px\;">Cost implications &amp\; co
 mparison (Using 2018 AWS $ rates in popular AWS region)</li>\n</ul>\n<p>E
 xamples will be provided in Java\, Javascript/NodeJS and will walk throug
 h the AWS DynamoDB SDK and console with examples for table creation\, CRU
 D operations\, capacity management\, accelerator cache cluster config and
  security group settings.</p>\n<p>&nbsp\;</p>\n<pre>Keywords: Cloud\, NoS
 QL\, Dynamo\, AWS\, DAX\, Amazon\, Web Services\, Storage\, Database\, Dy
 namoDB&nbsp\;</pre>
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