Amazon DynamoDB is a fully managed NoSQL database service provided by AWS that allows users to store and retrieve any amount of data in database tables. It automatically manages data traffic and maintains performance over multiple servers. DynamoDB is scalable, fast, durable, highly available, flexible, and cost-effective for customers. It relieves customers from the burden of operating and scaling their own distributed databases.

1. Intro

2. Amazon Dynamo DB
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▪ Amazon DynamoDB is a fully managed NoSQL
database service that allows to create database
tables that can store and retrieve any amount of
data.
▪ It automatically manages the data traffic of tables
over multiple servers and maintains performance.
▪ It also relieves the customers from the burden of
operating and scaling a distributed database.
▪ Hence, hardware provisioning, setup,
configuration, replication, software patching,
cluster scaling, etc. is managed by Amazon.

3. Benefits of AWS Dynamo DB
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▪ Scalable − Amazon DynamoDB is designed to scale.There is no need
to worry about predefined limits to the amount of data each table can
store. Any amount of data can be stored and retrieved. DynamoDB
will spread automatically with the amount of data stored as the table
grows.
▪ Fast − Amazon DynamoDB provides high throughput at very low
latency. As datasets grow, latencies remain stable due to the
distributed nature of DynamoDB's data placement and request
routing algorithms.
▪ Durable and highly available − Amazon DynamoDB replicates data
over at least 3 different data centers’ results.The system operates
and serves data even under various failure conditions.
▪ Flexible: Amazon DynamoDB allows creation of dynamic tables, i.e.
the table can have any number of attributes, including multi-valued
attributes.
▪ Cost-effective: Payment is for what we use without any minimum
charges. Its pricing structure is simple and easy to calculate.

4. Create DynamoDB Table
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▪ Step 1: Create a NoSQLTable
▪ In this step, you will use the DynamoDB console to create a
table.
– In the DynamoDB console, choose Create table.

5. Create DynamoDB Table
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– We will use a music library as our use case for this tutorial. In theTable
name box, type Music.

6. Create DynamoDB Table
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– The partition key is used to spread data across partitions for scalability.
It’s important to choose an attribute with a wide range of values and that
is likely to have evenly distributed access patterns.Type Artist in
the Partition key box.

7. Create DynamoDB Table
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– Because each artist may write many songs, you can enable easy sorting
with a sort key. Select the Add sort key check box.Type songTitle in
the Add sort key box.

8. Create DynamoDB Table
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– Next, you will enable DynamoDB auto scaling for your table.
– DynamoDB auto scaling will change the read and write capacity of your
table based on request volume. Using anAWS Identity and Access
Management (AWS IAM) role called DynamoDBAutoscaleRole,
DynamoDB will manage the auto scaling process on your behalf.
DynamoDB creates this role for you the first time you enable auto scaling
in an account.
– Instruct DynamoDB to create the role by clearing the Use default
settings check box.

9. Create DynamoDB Table
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– Scroll down the screen past Secondary indexes, Provisioned capacity,
andAuto Scaling to the Create button.We won't change these settings for
the tutorial.
– In the Auto Scaling section, notice that DynamoDB will create
the DynamoDBAutoscaleRole role for you.
– Now choose Create.
– When the Music table is ready to use, it appears in the table list with
a check box .
– Congratulations!You have created a NoSQL table using the DynamoDB
console.

10. Managing Indexes
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▪ Indexes give you access to alternate query patterns, and can
speed up queries.This section compares and contrasts index
creation and usage in SQL and DynamoDB.
▪ Whether you are using a relational database or DynamoDB, you
should be judicious with index creation.
▪ Whenever a write occurs on a table, all of the table's indexes
must be updated.
▪ In a write-heavy environment with large tables, this can
consume large amounts of system resources.
▪ In a read-only or read-mostly environment, this is not as much
of a concern—however, you should ensure that the indexes are
actually being used by your application, and not simply taking
up space.

11. Creating an Index
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▪ In DynamoDB, you can create and use a secondary index for
similar purposes.
▪ Indexes in DynamoDB are different from their relational
counterparts.When you create a secondary index, you must
specify its key attributes – a partition key and a sort key. After
you create the secondary index, you can Query it or Scan it just
as you would with a table. DynamoDB does not have a query
optimizer, so a secondary index is only used when you Query it
or Scan it.
▪ DynamoDB supports two different kinds of indexes:
– Global secondary indexes –The primary key of the index can be any two
attributes from its table.
– Local secondary indexes –The partition key of the index must be the
same as the partition key of its table. However, the sort key can be any
other attribute.

12. DynamoDB Query
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▪ Allow you to find items using only primary key values from
table or secondary index
▪ Benefits:
– Returns the item matching the primary key search
– Much more efficiency because it searches indexes only
– Returns all attributes of an item, or only the ones you want
– Is eventually consistent by default but can request a consistent read
– Can use conditional operators and filters to return precise results

13. DynamoDB Scan
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▪ Reads every item in the table and is operationally inefficient
▪ Looks for all items and attributes in a table by default
▪ Benefits;
– Scans can apply filters to the results to refine values
– Can return only specific attributes with
the ProjectionExpression parameter
▪ Negatives:
– The larger the data set in the table the slower performance of
a scan
– The more filters on the scan the slower the performance
– Returns only filtered results
– Only eventually consistent reads are available

14. DynamoDB Scans – If you must
use them
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▪ What you should keep in mind:
– You can reduce Page Size of an operation with
the Limit parameter, to limit how much data you try to
retrieve at the same time
– Avoid performing Scans on mission-critical tables
– Program your application logic to retry any requests that
receives a response code saying that you exceeded
provisioned throughput (or increase throughput)

15. DynamoDB & Provisioned
Throughput
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16. DynamoDB & Provisioned
Throughput
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▪ DynamoDB auto scaling actively manages throughput capacity for
tables and global secondary indexes. With auto scaling, you define a
range (upper and lower limits) for read and write capacity units.
▪ You also define a target utilization percentage within that range.
DynamoDB auto scaling seeks to maintain your target utilization,
even as your application workload increases or decreases.
▪ With DynamoDB auto scaling, a table or a global secondary index
can increase its provisioned read and write capacity to handle
sudden increases in traffic, without request throttling.
▪ When the workload decreases, DynamoDB auto scaling can
decrease the throughput so that you don't pay for unused
provisioned capacity.

17. DynamoDB & Provisioned
Throughput
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▪ If you aren't using DynamoDB auto scaling, you have to manually define
your throughput requirements. Provisioned throughput is the maximum
amount of capacity that an application can consume from a table or index.
If your application exceeds your provisioned throughput settings, it is
subject to request throttling.
▪ For example, suppose that you want to read 80 items per second from a
table.The items are 3 KB in size, and you want strongly consistent reads.
For this scenario, each read requires one provisioned read capacity unit.To
determine this, you divide the item size of the operation by 4 KB, and then
round up to the nearest whole number, as in this example:
▪ 3 KB / 4 KB = 0.75, or 1 read capacity unit
▪ For this scenario, you have to set the table's provisioned read throughput to
80 read capacity units:
▪ 1 read capacity unit per item × 80 reads per second = 80 read capacity units

18. DynamoDB & Provisioned
Throughput
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▪ Now suppose that you want to write 100 items per second to
your table, and that the items are 512 bytes in size. For this
scenario, each write requires one provisioned write capacity
unit.To determine this, you divide the item size of the
operation by 1 KB, and then round up to the nearest whole
number:
▪ 512 bytes / 1 KB = 0.5, or 1
▪ For this scenario, you would want to set the table's provisioned
write throughput to 100 write capacity units:
▪ 1 write capacity unit per item × 100 writes per second
= 100 write capacity units

19. Summary
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