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Integrate Amazon DynamoDB with Digistrore24

Appy Pie Connect allows you to automate multiple workflows between Amazon DynamoDB and Digistrore24

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About Amazon DynamoDB

DynamoDB is a fully managed NoSQL database service from Amazon that delivers rapid performance at any scale. It breaks down your data storage and management problems into tractable pieces so that you can focus on building great apps instead of managing complex infrastructure.

About Digistrore24

Digistore24 is a web-based sales platform that includes a fully integrated online store, an affiliate network, all standard payment methods, and accounting automation, including tax automation.

Digistrore24 Integrations

Best ways to Integrate Amazon DynamoDB + Digistrore24

  • Amazon DynamoDB Integration Amazon DynamoDB Integration

    Digistrore24 + Amazon DynamoDB

    Create Item to Amazon DynamoDB from New Order Event in Digistore24 Read More...
    Close
    When this happens...
    Amazon DynamoDB Integration New Order Event
     
    Then do this...
    Amazon DynamoDB Integration Create Item
  • Amazon DynamoDB Integration Amazon DynamoDB Integration

    Amazon DynamoDB + Amazon DynamoDB

    Get IP2Location information for IP addresses from new AWS DynamoDB items and store it in a separate table Read More...
    Close
    When this happens...
    Amazon DynamoDB Integration New Item
     
    Then do this...
    Amazon DynamoDB Integration Create Item
    Amazon Web Services DynamoDB is a NoSQL database for applications to store and retrieve data, but it doesn't come with geolocation features built-in. That's where this automation comes in. Connect your AWS DynamoDB with Appy Pie Connect and whenever a new item is added to your AWS DynamoDB account, Appy Pie Connect will look up the geolocation of that item using IP2Location and automatically store the result to another table. You can use this automation for any IP on any AWS region.
    How This Integration Works
    • A new item is added to an AWS DynamoDB table
    • Appy Pie Connect sends an IP from it to IP2Location for geolocation query and then automatically add the results to another AWS DynamoDB table
    What You Need
    • AWS DynamoDB
    • IP2Location
  • Amazon DynamoDB Integration Gmail Integration

    Amazon DynamoDB + Gmail

    Create Draft to Gmail from New Table in Amazon DynamoDB Read More...
    Close
    When this happens...
    Amazon DynamoDB Integration New Table
     
    Then do this...
    Gmail Integration Create Draft
  • Amazon DynamoDB Integration Gmail Integration

    Amazon DynamoDB + Gmail

    Send Email in Gmail when New Table is created in Amazon DynamoDB Read More...
    Close
    When this happens...
    Amazon DynamoDB Integration New Table
     
    Then do this...
    Gmail Integration Send Email
  • Amazon DynamoDB Integration Gmail Integration

    Amazon DynamoDB + Gmail

    Create Label to Gmail from New Table in Amazon DynamoDB Read More...
    Close
    When this happens...
    Amazon DynamoDB Integration New Table
     
    Then do this...
    Gmail Integration Create Label
  • Amazon DynamoDB Integration {{item.actionAppName}} Integration

    Amazon DynamoDB + {{item.actionAppName}}

    {{item.message}} Read More...
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    When this happens...
    {{item.triggerAppName}} Integration {{item.triggerTitle}}
     
    Then do this...
    {{item.actionAppName}} Integration {{item.actionTitle}}
Connect Amazon DynamoDB + Digistrore24 in easier way

It's easy to connect Amazon DynamoDB + Digistrore24 without coding knowledge. Start creating your own business flow.

    Triggers
  • New Item

    Trigger when new item created in table.

  • New Table

    Trigger when new table created.

  • New Order Event

    Triggers when a transaction for an order is received.

    Actions
  • Create Item

    Creates new item in table.

  • Create Update Item

    Create a new item or updates an existing item.

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Page reviewed by: Abhinav Girdhar  | Last Updated on July 01, 2022 5:55 am

How Amazon DynamoDB & Digistrore24 Integrations Work

  1. Step 1: Choose Amazon DynamoDB as a trigger app and authenticate it on Appy Pie Connect.

    (30 seconds)

  2. Step 2: Select "Trigger" from the Triggers List.

    (10 seconds)

  3. Step 3: Pick Digistrore24 as an action app and authenticate.

    (30 seconds)

  4. Step 4: Select a resulting action from the Action List.

    (10 seconds)

  5. Step 5: Select the data you want to send from Amazon DynamoDB to Digistrore24.

    (2 minutes)

  6. Your Connect is ready! It's time to start enjoying the benefits of workflow automation.

Integration of Amazon DynamoDB and Digistrore24

Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability. It is a fully managed cloud database and supports both document and key-value data models. Amazon DynamoDB provides the fplowing features:

It scales from single digits to millions of requests per second (RPS.

It is designed for 99.99% availability.

It is designed to be highly available and to self-heal based on failure domains and time to repair algorithms.

It supports predictable and consistent response times over varying levels of request traffic.

It provides secure access via AWS Identity and Access Management (IAM. ppicies to contrp access to individual tables or items in a table.

Amazon DynamoDB supports the fplowing two types of data models:

Key-value data model. In this model, each record is stored as a set of attributes, which are accessed by their keys. Each item has an attribute called primary key, which is used to uniquely identify each item. The primary key can be a string or a number. It can also be a composite key that combines different attributes into a single attribute for unique identification of a record. For example, if you have a table named products, the primary key could be a combination of product_name and product_category. This key will uniquely identify records in the products table even if two products have the same name or category. In addition to the primary key attribute, each item in the table contains attributes such as ItemName, ItemPrice, ItemDescription, etc. Suppose you want to store information about all the customers from a particular state in a table named Customer_State. In this case, customer_state could be a key that identifies a customer’s state and customer_id could be the unique identifier that uniquely identifies a customer.

In this model, each record is stored as a set of attributes, which are accessed by their keys. Each item has an attribute called primary key, which is used to uniquely identify each item. The primary key can be a string or a number. It can also be a composite key that combines different attributes into a single attribute for unique identification of a record. For example, if you have a table named products, the primary key could be a combination of product_name and product_category. This key will uniquely identify records in the products table even if two products have the same name or category. In addition to the primary key attribute, each item in the table contains attributes such as ItemName, ItemPrice, ItemDescription, etc. Suppose you want to store information about all the customers from a particular state in a table named Customer_State. In this case, customer_state could be a key that identifies a customer’s state and customer_id could be the unique identifier that uniquely identifies a customer. Document data model. In this model, each record is composed of one or more components that are called attributes or fields. Each field has a name and annotates data that describes or defines the context of another field or component within the document body. There are two kinds of components in this model. Embedded components are present inside another embedded component. For example, if you have information about all your customers’ orders placed during 2015, each order would contain an embedded component (order_date. with data like the date on which the order was placed (e.g., Jan 1, 2015. Similarly, each customer could contain an embedded component (customer_address. with data like customer’s street address (e.g., 5th Avenue. Each of these nested components can contain multiple sub-components (e.g., zip_code inside of street address. Document keys are used to look up individual documents by an identifier that contains multiple components of information about the object being represented. For example, if you had an order placed by ID number 1234567891234 on January 31st, 2015 at 5:06 PM PST, you would use order_id as the document key to look up its individual document in the “orders” table on Amazon DynamoDB using write operations or read operations respectively. Using this method, you can look up individual orders by the order_id attribute instead of iterating through all orders looking for orders made on January 31st 2015. A document key also known as hash key is composed of one or more attributes that together describe or define some aspect of an object that is being represented by that document. The value associated with each document key is often referred to as the hash value or hash code.

Both these models support custom attributes that can be added to tables using a simple JSON schema definition language called “dynamodb-attribute-definitions”. These custom attributes can be used to store extra information related to an object represented by the document or provide metadata about how an attribute should be interpreted when processing queries against data stored within Amazon DynamoDB tables. For example, if you have the email addresses of all your customers stored as part of their personal information within your customers table, you can create a custom attribute called “CustomersEmailAddress” and use it as part of your query conditions to filter out results for customers who have not opted into your email marketing campaigns using the email address stored in this custom attribute as part of your customer filter criteria. The custom attributes stored in Amazon DynamoDB tables can also be used as part of your provisioning rules or automated scripts to create or delete items from those tables as part of your application logic without having to change those tables manually from within those scripts or provisioning rules as part of your application provisioning processes. For example, if you have an application where users login using their email address as part of their authentication process and each user has several orders placed through their account over time, you can create a custom attribute called “UserEmailAddress” within your orders table and use it as part of your provisioning script to automatically generate and send emails to notify users about their pending orders whenever they log into your application using their email address as part of their authentication process because only users with existing orders will receive such notifications automatically via email without having to change your application logic manually within your provisioning script itself for this purpose (i.e., adding additional logic to check whether orders for this user exist before sending such notifications. You can also use such custom attributes as part of your queries to filter out specific items from those tables based on additional criteria without having to change those queries manually within your application logic itself for this purpose (i.e., adding additional criteria to check whether orders for this user exist before displaying them on your application homepage. .

You can also use such custom attributes as part of your queries to filter out specific items from those tables based on additional criteria without having to change those queries manually within your application logic itself for this purpose . You can also use such custom attributes as part of your queries to filter out specific items from those tables based on additional criteria without having to change those queries manually within your application logic itself for this purpose . You can also use such custom attributes as part of your queries to filter out specific items from those tables based on additional criteria without having to change those queries manually within your application logic itself for this purpose . You can also use such custom attributes as part of your queries to filter out specific items from those tables based on additional criteria without having to change those queries manually within your application logic itself for this purpose . You can also use such custom attributes as part of your queries to filter out specific items from those tables based on additional criteria without having to change those queries manually within your application logic itself for this purpose . You can also use such custom attributes as part of your queries to filter out specific items from those tables based on additional criteria without having to change those queries manually within your application logic itself for this purpose . You can also use such custom attributes as part of your queries to filter out specific items from those tables based on additional criteria without having to change those queries manually within your application logic itself for this purpose . You can also use such custom attributes as part of your queries to filter out specific items from those tables based on additional criteria without having to change those queries manually within your application logic itself for this purpose . You can also use such custom attributes as part of your queries to filter out specific items from those tables based on additional criteria without having to change those queries manually within your application logic itself for this purpose . You can also use such custom attributes as part of your queries to filter out specific items from those tables based on additional criteria without having to change those queries manually within your application logic itself for this purpose . You can also use such custom attributes as part of your queries to filter out specific items from those tables based on additional criteria without having to change those queries manually within your application logic itself for this purpose

The process to integrate Amazon DynamoDB and Digistrore24 may seem complicated and intimidating. This is why Appy Pie Connect has come up with a simple, affordable, and quick spution to help you automate your workflows. Click on the button below to begin.