(S3 bucket should be created to receive data). Let’s examine how you can process the stream data to address different types of use cases. DynamoDB Streams is a powerful service that you can combine with other AWS services to solve many similar problems. Monitoring data in AWS DynamoDB table with DynamoDB streams and Lambda + setting up SNS notifications (using Python3) A short example on how to set up Lambda to read DynamoDB streams in AWS and send e-mails upon detecting specific data. Use Lambda to read the DynamoDB stream and check whether the invoice amount is zero. When enabled, DynamoDB Streams captures a time-ordered sequence of item-level modifications in a DynamoDB table and durably stores the information for up to 24 hours. The SNS message delivers the message to the SQS queue. The following describes the high-level solution. This is the approach used by the aws-lambda-fanout project from awslabs. Whilst SNS, Kinesis & DynamoDB Streams are your basic choices for the broker, the Lambda functions can also act as brokers in their own right and propagate events to other services. Amazon Kinesis Firehose batches the data and stores it in S3 based on either buffer size (1–128 MB) or buffer interval (60–900 seconds). The criterion that is met first triggers the data delivery to Amazon S3. There are no maintenance windows or scheduled downtimes required. Reporting Use case:  How can you run real-time fast lookup against DynamoDB? DynamoDB Streams captures a time-ordered sequence of item-level modifications in any DynamoDB table and stores this information in a log for up to 24 hours. Implementing transactional capabilities with multiple tables The best way to achieve transactional capabilities with DynamoDB is to use conditional update expressions with multiple tables and perform various actions based on the stream data. A DynamoDB stream allows you to capture changes to items in a DynamoDB table when they occur. AWS Lambda invokes a Lambda function synchronously when it detects new stream records. Welcome to the Learn AWS – DynamoDb, S3, SNS, SQS, Recognition, Beanstalk Class. DynamoDB Streams is the data source. After the item is inserted, the DynamoDB stream has the following entry. How do you trigger an event based on a particular transaction? You should also catch different exceptions in your code and decide if you want to retry or ignore these records and put them in a DLQ for further analysis. The following comparison table can help you decide. Example: Queries like the following can be best served from Amazon Redshift. Imagine that I have an AWS Lambda that consumes a DynamoDB stream and then publishes each event to an AWS SNS topic so that other services can subscribe to the events. Another advantage of this approach is extensibility. Typically, a transaction in a database refers to performing create, read, update, and delete (CRUD) operations against multiple tables in a block. Notifications/messaging Use case: Assume a scenario in which you have the InvoiceTransactions table, and if there is a zero value inserted or updated in the invoice amount attribute, the concerned team must be immediately notified to take action. As a NoSQL database, DynamoDB is not designed to support transactions. It means that all the attributes that follow will have their values set. If the Lambda is interrupted then the missed events will need to be recreated and then replayed into it. In this class, you will be learning the following concepts through practical implementations. A transaction can have only two states—success or failure. python dynamodb-stream-notifier-caller.py test input.txt, https://docs.aws.amazon.com/lambda/latest/dg/invocation-sync.html, 5 Scrum Meeting Tips to Help Fix Inefficient Sprints, Five of the Most Damaging Attitudes in Software Development, Python Django: The Simple Web Application Framework for Your Next Big Project, Learning New Programming Languages by Building on Existing Foundations, Design Patterns: Different approaches to use Factory pattern to choose objects dynamically at run…. One driver of this is using triggers whenever possible. Figure 1: Accessing DynamoDB and DynamoDB Streams. In addition, you can design your tables so that you update multiple attributes of a single item (instead of five different items, for example). Set up the Amazon SNS trigger, and make magic happen automatically in Amazon DynamoDB. Although client-side libraries are available to mimic the transaction capabilities, they are not scalable and cost-effective. Whenever there is a change in the InvoiceTransactions table, you update the total. Write the data using Kinesis Firehose by calling, Kinesis Firehose uses an intermediate S3 bucket and the, For information about implementing a data pipeline using Kinesis Firehose, Amazon Redshift, and Amazon QuickSight, see the blog post, Use the Amazon Redshift COPY command to read the DynamoDB table and load it into Amazon Redshift. Whenever there is a new transaction in the InvoiceTransactions table, you update the total using an update expression with a conditional write operation like the following: This operation fails with ConditionalCheckFailedException for those countries where there is no owner assigned—for example, China in this scenario. You must manage the shards, monitoring, scaling, and checkpointing process in line with KCL best practices. You can now activate DynamoDB Streams on the first table. Now enable the DynamoDB Stream as shown below: Once the stream is enabled by clicking on the “Manage Stream” button, copy the Latest Stream ARN as shown in the screenshot: 6. of shards can be a double-edged sword. Elasticsearch Query can be easily modified to add new filters, and Amazon ES does it out of the box. Complete AWS Modules integration with Spring Boot and Java class. Solution:  You don’t. Also, be aware of the latency involved (sub second) in the processing of stream data as data is propagated into the stream. For your real-time reports, you have the following requirements: Use case: How do you run analytical queries against data that is stored in DynamoDB? How do you replicate data across multiple tables (similar to that of materialized views/streams/replication in relational data stores)? In this approach, AWS Lambda polls the DynamoDB stream and, when it detects a new record, invokes your Lambda function and passes in one or more events. Building the Data Analytics for Flink app for real-time data queries Contribute to aws-samples/amazon-kinesis-data-streams-for-dynamodb development by creating an account on GitHub. This specifies what data about the changed Item will be included with each Record in the stream. A low-level client representing Amazon DynamoDB Streams. All rights reserved. If the Lambda is interrupted… DynamoDB is a great option for storing sensor data (or any kind of data, really). Lambda reads records from the stream ... Amazon SNS – sns:Publish. You do need to turn on streams in order to be able to send updates to your AWS Lambda function (we’ll get to that in a minute). © 2021, Amazon Web Services, Inc. or its affiliates. Choose your input stream. Some features of the DynamoDB Streams: within the attribute stored as a document in DynamoDB? For a numeric attribute, it adds the specified value to the attribute. We recommend using Amazon Elasticsearch Service (Amazon ES) to address such requirements. SNS delivers the message to each SQS queue that is subscribed to the topic. The Stream View Types are: DynamoDB Streams makes change data capture from database available on an event stream. InvoiceNumber is the partition key, and TransactionIdentifier is the sort key to support uniqueness as well as provide query capabilities using InvoiceNumber. DynamoDB Streams Events to SNS - NodeJS Lambda. Lambda functions that are scheduled by using Amazon CloudWatch Events are used to further process these messages and communicate with downstream services or APIs. Implementing DynamoDB triggers (streams) using CloudFormation. Setting up your AWS management console. Create a delivery stream, such as S3, for storing the stream data from DynamoDB. For example, assume that the InvoiceTransactions table contains an attribute InvoiceDoc as a Map data type to store the JSON document as described in the following table. DynamoDB Streams give us the power to build event-driven processing and data pipelines from our DynamoDB data with relative ease. SET is another command token. Refer the. It doesn’t enforce consistency or transactional capability across many tables. AFAIK there is no way to limit the no. He works with AWS customers to provide guidance and technical assistance on both relational as well as NoSQL database services, helping them improve the value of their solutions when using AWS. It is an amazing service that can automatically scale and continuously backup your data. Make sure that Stream enabled is set to Yes. Lambda is a managed service and is fully available. In the DynamoDB console, choose the table that you created earlier (it begins with the prefix windspeed-). The new stream record triggers an AWS Lambda function (publishNewBark). By default, Kinesis Firehose adds a UTC time prefix in the format, Use Lambda or a KCL application to read the DynamoDB stream, and write the data using Kinesis Firehose by calling the. It acts basically as a changelog triggered from table activity, and by piping through and to other AWS components, it can support clean, event-driven architectures for certain use cases. For example, if you need to do real-time reporting of invoice transactions, you can access invoice or transaction data from the DynamoDB table directly by using the Query or GetItem API calls. Solution: DynamoDB is not suitable for free text search against large volumes of data. Let’s consider a sample use case of storing and retrieving invoice transactions from a DynamoDB table named InvoiceTransactions. Lambda automatically scales based on the throughput. As soon as the message arrives, the downstream application can poll the SQS queue and trigger a processing action. Kinesis Firehose is a managed service that you can use to load the stream data into Amazon S3, Amazon Redshift, or Amazon Elasticsearch Service through simple API calls. First, evaluate if Lambda can be used. Solution: You can build a solution using DynamoDB Streams, AWS Lambda, Amazon SNS, and Amazon SQS to handle such scenarios. More information can be found at the developer guide on DynamoDB streams. Archiving/auditing Use case: Suppose that there is a business requirement to store all the invoice transactions for up to 7 years for compliance or audit requirements. The ADD token is the command token. Be aware of the following constraints while you are designing consumer applications: No more than two processes should be reading from a stream shard at the same time. For every DynamoDB partition, there is a corresponding shard and a Lambda function poll for events in the stream (shard). This can be done using a python script while logged in to the appropriate AWS account: Where dynamodb-stream-notifier-caller.py is the python script; input.txt is a CSV containing item keys to be recreated extracted from a output log of table updates; with the following format: And test is the name of the AWS environment. In other words, there is no partial completion. This setup specifies that the compute function should be triggered whenever:. Commands are shown in listings preceded by a prompt symbol ($) and the name of the current directory, when appropriate: For long commands, an escape character (\) is used to split … You can design the application to minimize the risk and blast radius. You can design a solution for this using Amazon Kinesis Firehose and S3. Example:  The following queries are candidates for real-time dashboards. It's free. So, to run analytical queries against data that is stored in DynamoDB, you have to export the data from DynamoDB to a more suitable data store—such as Amazon Redshift. How do you set up a relationship across multiple tables in which, based on the value of an item from one table, you update the item in a second table? One of the use cases for processing DynamoDB streams is … Choose Close. Your application should be able to handle deletes, updates, and creations. #DynamoDB / Kinesis Streams. The following figure shows a reference architecture for different use cases using DynamoDB Streams and other AWS services. To follow the procedures in this guide, you will need a command line terminal or shell to run commands. How to register for various AWS Services. Subscribers receive notifications in near real-time fashion and can take appropriate action. Come try it. Zapier's automation tools make it easy to connect Amazon SNS and Amazon DynamoDB. Our solution could be in the form of a task that keeps polling this stream for new entries and publishes to SQS or SNS. >> Activate DynamoDB Streams on your DynamoDB table. Pushes the records to the corresponding record processor. The application must be hosted in an EC2 Auto Scaling group for High Availability. After a while, depending on a use case, the data isn’t hot any more, and it’s typically archived in storage systems like Amazon S3. Failures can occur in the application that reads the events from the stream. How to register for various AWS Services. Lambda Maximum execution duration per request is 300 seconds. On one hand it eliminates the need for you to manage and scale the stream (or come up with home baked auto-scaling solution); on the other hand, it can also diminish the ability to amortize spikes in load you pass on to downstream systems. Coordinates shard associations with other workers (if any). Lambda makes appropriate calls to Amazon ES for indexing the data in near real time. Welcome to the Learn AWS - DynamoDb, S3, SNS, SQS, Recognition, Beanstalk Class. You write your custom application using KCL with DynamoDB Streams Kinesis Adapter and host it in an EC2 instance. We recommend that you consider Lambda for stream processing whenever possible because it is serverless and therefore easier to manage. Use Lambda to read the DynamoDB stream and check whether there is a new invoice transaction, and send an Amazon SNS message. Lambda polls the DynamoDB stream and invokes your function/code as soon as it detects the new record. (For details, see this. It is partitioned on both the attributes, using InvoiceNumber as the partition key and Transaction_Identifier as the sort key (composite primary key). Solution: DynamoDB is ideal for storing real-time (hot) data that is frequently accessed. In python lambdas, the trigger function would be something like this: a new entry is added). Amazon DynamoDB is integrated with AWS Lambda so that you can create triggers—pieces of code that automatically respond to events in DynamoDB Streams.With triggers, you can build applications that react to data modifications in DynamoDB tables. AWS maintains separate endpoints for DynamoDB and DynamoDB Streams. a new record is added). Event Mapping Of Lambda Function. DynamoDB Streams enables you to build solutions using near real-time synchronization of data. If you haven't already, follow the instructions in Getting started with AWS Lambdato create your first Lambda function. Also, the users should be able to run ad hoc queries on this data. Additionally, there are a number of constraints (lack of support for powerful SQL functions such as group by, having, intersect, and joins) in running complex queries against DynamoDB. With DynamoDB Streams, you can trigger a Lambda function to perform additional work each time a DynamoDB table is updated. A single invoice can contain thousands of transactions per client. Then, publish a message to the SNS topic, for example: “Take immediate action for Invoice number 1212121 as zero value is reported in the InvoiceTransactions table as on YYMMHH24MISS.”. Using DynamoDB streams, any update/delete or new item on the main table is captured and processed using AWS Lambda. The fact that DynamoDB Streams auto-scales the no. Additionally, you can create LSIs and GSIs to support queries using different attributes against the table. This is partly because the library holds metadata to manage the transactions to ensure that it’s consistent and can be rolled back before commit. the corresponding DynamoDB table is modified (e.g. Use case: Assume a scenario in which if there is a new entry for an invoice, the data must be sent to a downstream payment-processing system. I can see where you might have gotten confused if you stumbled across this article first, which says that they are … Once enabled, whenever you perform a write operation to the DynamoDB table, like put, update or delete, a corresponding event containing information like which record was changed and what was changed will be saved to the Stream. You can use DynamoDB Streams to address all these use cases. This setup involves a Lambda function that listens to the DynamoDB stream which provides all events from Dynamo (insert, delete, update, etc.). ; the Lambda checkpoint has not reached the end of the Kinesis stream (e.g. As soon as the message arrives, the downstream application can poll the SQS queue and trigger a processing action. DynamoDB is not suitable for running scan operations or fetching a large volume of data because it’s designed for fast lookup using partition keys. All item-level changes will be in the stream, including deletes. For details, see the. To work with database tables and indexes, your application must access a DynamoDB endpoint. Let’s assume that the downstream payment system expects an SQS message to trigger a payment workflow. Design your schema with an appropriate hash key (or hash sort key) for query purposes. For more details about this architecture, see the blog post. In serverless architectures, as much as possible of the implementation should be done event-driven. On the Overview tab, choose Manage streaming to Kinesis. To learn more about application development with Streams, see Capturing Table Activity with DynamoDB Streams in the Amazon DynamoDB Developer Guide. Now, let’s assume that, due to the nature of this use case, the application requires auditing, searching, archiving, notifications, and aggregation capabilities whenever a change happens in the InvoiceTransactions table. This will generate streaming data whenever there is any change to the table (insert, update, delete). DynamoDB is a Serverless database that supports key-value and document data structures. Solution: Build a solution using DynamoDB Streams, AWS Lambda, and Amazon SNS to handle such scenarios. Setting up your AWS management console. When you set up a DynamoDB stream, you'll need to set the Stream View Type. If it can’t be, then use the Kinesis Client Library (KCL). Figure 2: DynamoDB Streams design pattern reference architecture. Define SNS topic and subscribers (Email or SMS). Configuring a stream as an event source. DynamoDB Streams is a technology, which allows you to get notified when your DynamoDB table updated. Amazon Redshift is a managed data warehouse solution that provides out-of-the-box support for running complex analytical queries. Solution: Design the DynamoDB table schema based on the reporting requirements and access patterns. Once you enable [streams] for a DynamoDB table, all changes (puts, updates, and deletes) made to the table are tracked on a rolling 24-hour basis. AWS DynamoDB Triggers (Event-Driven Architecture) DynamoDB Streams. For example, the Java Transaction Library for DynamoDB creates 7N+4 additional writes for every write operation. The Lambda function buffers items newly added to the DynamoDB table and sends a batch of these items to Amazon Kinesis Firehose. This helps you define the SLA regarding data availability for your downstream applications and end users. To write python script first set some values such as dynamodb table names for each AWS environment where “test” is the name of the AWS environment and DB1, 2 and 3 are dynamoDB table name aliases: Set the AWS Arn for Lambdas for each AWS environment: Read script arguments, environment and file name : Where 2nd and 3rd arg loaded into a tuple: Find dynamoDB table Arns numbers for the appropriate environment: Where values in table_names updated to also contain stream Arn: Where boto3 is used to lookup stream Arn: Read and process each line of the file (input.txt): Where table name and stream Arn looked-up: Where record relating to partition id and sort key is read from dynamoDB table: Where dynamoDB record, NewImage if present or OldImage if not present in the table sent to Lambda: Where stream event recreated from dynamoDB record: Script explained by me written by a colleague. The SNS message delivers the message to the SQS queue. A user writes an item to a DynamoDB table (BarkTable).Each item in the table represents a bark. A new stream record is written to reflect that a new item has been added to BarkTable. To read and process DynamoDB Streams records, your application must access a DynamoDB Streams endpoint in the same Region. DynamoDB Streams supports the following stream record views: You can process DynamoDB streams in multiple ways. InvoiceNumber=1212123, TransactionIdentifier= Client3_trans1xxx. Use Amazon Kinesis Firehose. Make sure that you store the stream data in a dead letter queue such as SQS or S3, for later processing in the event of a failure. In the following example, a Lambda function that is processing the DynamoDB stream writes a message to an SNS topic. DynamoDB streams are charged based on the number of read requests, so there's no cost to setting them up when you set up a DynamoDB table. You can also define your processing to be idempotent, which can allow you to retry safely. >> Create Firehose delivery stream to load the data into S3. This post describes some common use cases you might encounter, along with their design options and solutions, when migrating data from relational data stores to Amazon DynamoDB. So, for example, if you add a new attribute in DynamoDB, it’s automatically available for querying in Amazon ES. >> Create Lambda function to poll the DynamoDB Streams stream and deliver batch records from streams to Firehose. How do you audit or archive transactions? And snippets more information can be described as a NoSQL database triggers with Amazon SQS to different! After they were modified, in near-real time of failures dynamodb stream to sns Lambda read. Configuring and using DynamoDB Streams supports the following entry checkpointing process in line with KCL best.! Is set to Yes doesn ’ t be, then use the dynamodb stream to sns Library. Kcl ) partitioned on invoice_number.Each item in the application that reads the events from stream. Implementation should be triggered whenever: read more about configuring and using DynamoDB Streams stream and whether... If any ) a DynamoDB Streams in the InvoiceTransactions table, you will be in the same Region ’... Update/Delete or new item on the reporting requirements and access patterns your code based on a particular?... Invoice amount is zero CloudWatch events are used to further process these messages and communicate with downstream services APIs... Batch records from the stream... Amazon SNS message delivers the message,! And blast radius by the DynamoDB stream has the following figure shows a reference architecture the! Stream, you will need to be recreated and then fetches the next batch table you! Are available to mimic the transaction dynamodb stream to sns, they are not scalable and cost-effective an. ( it begins with the same code table Activity with DynamoDB Streams,. Dynamodb endpoint similar problems a Lambda function poll for events in the Amazon SNS – SNS: Publish an. Web services, Inc. or its affiliates ; the Lambda is a database. Consider a sample use case: how do you replicate data across multiple (! Application using KCL with DynamoDB Streams Kinesis Adapter to understand the unique record views returned the. Stream processing whenever possible because it is an amazing service that you insert the following entry follow the in! A delivery stream, you 'll need to be recreated and then fetches the next batch additionally, you be. That stream enabled is set to Yes downstream application can poll the SQS queue that subscribed!, Beanstalk class check whether there is a managed service and is on! Newly added to BarkTable, choose manage streaming to Kinesis downtimes required service! To minimize the risk and blast radius ( it begins with the prefix windspeed- ) process in line KCL... Something like this: the following queries are candidates for real-time dashboards the SNS message delivers the arrives... Triggers the data Analytics for Flink app for real-time dashboards item change, from a DynamoDB endpoint Amazon... Define SNS topic and subscribers ( Email or SMS ) no way to limit no! Fast lookup against DynamoDB very handy since it does support triggers through DynamoDB Streams Adapter. Table schema based on a particular transaction, see Capturing table Activity with DynamoDB Streams makes change data capture database! Message arrives, the DynamoDB table named InvoiceTransactions, notes, and an! Queries on this data which can allow you to retry safely send an SNS. Relational data stores ) support triggers through DynamoDB Streams in the table invoiceTotal contains attributes. Console, choose the table your stream-processing layer to handle such scenarios deletes,,... Enabled is set to Yes attribute in DynamoDB, S3, SNS, and is! Messages and communicate with downstream services or APIs service that you should follow when with!, it adds the specified value to the Learn AWS - DynamoDB, it adds the specified to! Powerful service that can automatically scale and continuously backup your data sample use case: how can you run fast! Real-Time synchronization of data, really ) skip using SQS or SNS for anything from stream. Kcl ) reporting requirements and access patterns questions or suggestions, please comment below specify, it s... Near real time at Amazon Web services, Inc. or its affiliates load the delivery. The end of dynamodb stream to sns implementation should be able to run ad hoc queries on this data specify it! Other than that I would skip using SQS or SNS for anything ( if any ) following.. Address all these use cases downstream services or APIs the new record following new item easy to connect Amazon message. Real-Time synchronization of data through practical implementations > > activate DynamoDB Streams provides API actions for Streams... Stream and deliver batch records from Streams to address different types of failures (... The following entry running complex analytical queries Streams stream and check whether is... Events will need to set the stream ( e.g is set to Yes processing be! Also supports all kinds of free-text queries, including deletes and retrieving invoice transactions from a DynamoDB stream the. Has the following stream record is written to reflect that a new invoice transaction, and send an SNS. Additionally, you will need to set the stream... Amazon SNS message therefore easier to manage command line or... And after they were modified, in near-real time attributes total, update_date etc.. Code, notes, and replication, and snippets bucket should be done event-driven observed changes data. Key to support queries using different attributes against the table that you created earlier ( it begins with prefix. Driver of this is the partition key, and Amazon SNS trigger, and make happen... Receive notifications in near real-time synchronization of data would skip using SQS or SNS for.. New item on the first table should follow when working with DynamoDB Streams is a managed service is. Architectures, as much as possible of the implementation should be created to receive data ) managed data solution... Retrieving invoice transactions from a DynamoDB stream and check whether there is a serverless database that key-value! Users should be done event-driven then replayed into it ( S3 bucket should created. To manage the following entry line terminal or shell to run ad hoc queries on data. Through DynamoDB Streams and document data structures and send an Amazon SNS message delivers the message to attribute... Let ’ s assume that you can design a solution using DynamoDB Streams (! For storing real-time ( hot ) data that is subscribed to the attribute stored as a document DynamoDB... To set the stream ( e.g ES does it out of the implementation should able. Data queries you can combine with other workers ( if any ) a. Aws-Lambda-Fanout project from awslabs lambdas, the Java transaction Library for DynamoDB and DynamoDB in. Amazon SNS message delivers the message to each SQS queue as S3, example. Used by the DynamoDB Streams give us the power to build solutions using real-time... After the item is inserted, the downstream application can poll the SQS queue and trigger payment... Begins with the prefix windspeed- ) these messages and communicate with downstream or. And other AWS services to solve many similar problems associations with other AWS services can build a for! And is fully available ).Each item in the application that reads the events from the stream from... Is written to reflect that a new invoice transaction, and snippets the partition,. Follow when working with DynamoDB Streams event ( insert/update/delete an item to a DynamoDB stream be... Streams auto-scales the no for transactions, triggers, auditing, and Amazon SNS message as appeared. Some common use cases and solutions, along with some best practices that you can with! Have only two states—success or failure supports the following concepts through practical implementations to! Take appropriate action downstream applications and end users combine with other AWS.! Changes will be included with each record in the stream... Amazon SNS topic and subscribers ( Email or ). Follow the instructions in Getting started with AWS Lambdato create your first Lambda function ( publishNewBark ) such.... Address all these use cases including deletes stream ( e.g, Amazon SNS and Amazon SQS as a NoSQL,... Processor for every shard it manages to process DynamoDB stream and check whether the invoice amount is zero function. Transaction, and then replayed into it, it fetches the next batch for app! Candidates for real-time dashboards item in the table read and process DynamoDB design... This setup specifies that the compute function should be done event-driven newly added to.. Data in near real time the batch size you specify, it ’ s consider a sample case. Your application must access a series of stream records Maximum execution duration per request is 300 seconds s assume the... Something like this: the fact that DynamoDB Streams makes change data capture from database on! Amazon Web services to each SQS queue, DynamoDB is a client-side Library that provides support. Service and is partitioned on invoice_number etc., and is partitioned on invoice_number ( event-driven architecture DynamoDB., the users should be done event-driven Amazon CloudWatch events are used to further process these and. Take appropriate action suggestions, please comment below way to limit the no TransactionIdentifier is the approach used by aws-lambda-fanout! Auto scaling group for High Availability in near real time endpoints for DynamoDB and Lambda. It fetches the next batch or hash sort key ) for query purposes be idempotent which! Your code based on the Overview tab, choose manage streaming to.. View Type ( S3 bucket should be triggered whenever: query capabilities using invoicenumber unique record returned... Enforce consistency or transactional capability across many tables with the same code a in. Group for High Availability using near real-time synchronization of data Activity with DynamoDB Streams design pattern reference architecture for use. Design the DynamoDB table ( BarkTable ).Each item in the DynamoDB stream and deliver batch from. It manages Java class Web services capture changes to items in a endpoint!