?>

MongoDB Realm + Woodpecker.co Integrations

Appy Pie Connect allows you to automate multiple workflows between MongoDB Realm and Woodpecker.co

About MongoDB Realm

database that makes it really easy to iterate and store non-relational data. No more crazy SQL queries and ALTER tables to add extra data!

About Woodpecker.co

B2B companies directly contact prospective clients by automated sending of personalized sales emails and follow-ups. Send emails and follow-up sequences automatically from your mailbox and have all the replies detected. Grow your business within the Predictable Revenue methodology

Woodpecker.co Integrations
Connect MongoDB Realm + Woodpecker.co in easier way

It's easy to connect MongoDB Realm + Woodpecker.co without coding knowledge. Start creating your own business flow.

    Triggers
  • New Push notification

    Triggers when a new push notification is created

  • New Service

    Triggers when a new service is created

  • New User

    Triggers when a new user is created

  • Email Opened

    Triggers when a prospect opens your email.

  • Email Sent

    Triggers when Woodpecker sends an email to prospect from campaign.

  • Link Clicked

    Triggers when a prospect clicks on a link in your email.

  • Prospect Blacklisted

    Triggers when a prospect status is changed to BLACKLISTED manually or when prospect unsubscribes from Woodpecker.

  • Prospect Bounced

    Triggers when a prospect’s email address bounces your message and the prospect status gets changed to BOUNCED in Woodpecker

  • Prospect Interested

    Triggers when you mark a prospect who replied as INTERESTED.

  • Prospect Invalid

    Triggers when a prospect’s email address doesn't exist on an external server. This check happens when Woodpecker tries to send an email to this prospect. Status is changed to INVALID in Woodpecker.

  • Prospect Maybe Later

    Triggers when you mark a prospect who replied as MAYBE LATER.

  • Prospect Not Interested

    Triggers when you mark a prospect who replied as NOT INTERESTED.

  • Prospect Replied

    Triggers when a prospect replies to your email or is manually marked as REPLIED in Woodpecker.

    Actions
  • Confirm Pending User

    Confirm a pending user

  • Create Service

    Create a service

  • Create Trigger

    Creates a Trigger

  • Create User

    Creates a User

  • Delete Push Notification

    Delete a pus notification

  • Delete Trigger

    Delete a trigger

  • Delete User

    Delete a User

  • Disable User

    Disable a User

  • Enable User

    Enable a User

  • Update Trigger

    Update a trigger

  • Create or Update Prospect

    Adds a new prospect or Updates existing prospect in the list of Prospects.

  • Create or Update Prospect in Campaign

    Adds a new prospect or updates existing prospect's data in a campaign of choice.

  • Stop Follow Ups

    Stop follow-ups planned for this prospect.

How MongoDB Realm & Woodpecker.co Integrations Work

  1. Step 1: Choose MongoDB Realm as a trigger app and Select "Trigger" from the Triggers List.

    (30 seconds)

  2. Step 2: Authenticate MongoDB Realm with Appy Pie Connect.

    (10 seconds)

  3. Step 3: Select Woodpecker.co as an action app.

    (30 seconds)

  4. Step 4: Pick desired action for the selected trigger.

    (10 seconds)

  5. Step 5: Authenticate Woodpecker.co with Appy Pie Connect.

    (2 minutes)

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

Integration of MongoDB Realm and Woodpecker.co

MongoDB Realm

MongoDB Realm is a free, open-source, on-premise database that runs on the JVM and provides user-friendly API. It is an object-document mapping library that connects MongoDB server to Java objects. Object-Document Mapping (ODM. is a technique of mapping data between object-oriented and relational databases (RDBMS. An ODM defines the structure of data in the document formats.

Woodpecker.co

Woodpecker.co is a rich in features but simple in use website builder from Odessa, Ukraine. Woodpecker.co was established in 2015 as the project for creating a website for the Odessa Hackfest. The project evpved into a complete platform for creating websites for any industry and purpose. As the result, Woodpecker.co is an open source content management system (CMS. based on PHP Laravel framework. Woodpecker.co CMS comes with many features and modules that allow you to create modern websites easily and quickly, without any additional knowledge in web development and web design. Woodpecker.co allows its users to create their own style with custom visual or HTML templates and CSS. In addition, Woodpecker.co sites have access to premium plugins and themes from the marketplace, which makes possible to create unique sites with any design and style.

Integration of MongoDB Realm and Woodpecker.co

There are two ways to integrate MongoDB Realm and Woodpecker.co. Caching and Data storage. For caching, we need to redirect requests to Woodpecker.co/api/cache/v1/data/Woodpecker/<db_name> to Woodpecker.co/api/cache/v1/data/<db_name>. For storing data, we need to redirect requests to Woodpecker.co/api/data/Woodpecker/<db_name> to Woodpecker.co/api/data/<db_name>. Let’s consider these ways in more detail.

Caching

Caching is a temporary storage of data for a certain period of time and it significantly improves overall performance of your website by reducing latency and increasing speed. Since it is a temporary storage, it is very important not to store it when it is not necessary to do so. In other words, cache should be invalidated only when the data change and reloaded from the original source (or next level cache. when the data are updated again. That’s why we need to keep track of changes in our database when they occur. How can we make sure that changes occurred? Each time an update occurs in our database, we need to add an event listener for a specific event into our application, so that we will know when the changes occurred and what happened with our data afterwards. When this event occurs, we will send a request to Woodpecker.co’s API to refresh the cached data from the database. All changes made will be tracked and cached in our database. Thus, whenever there is a request for data from our API, we need to first check if they are available in the cache or not. If they are not available in the cache, we will fetch them from the database where they are stored and save them into the cache for future usage by our application or client’s requests. If they are available in the cache, we will return them to our application or client’s requests immediately without asking for the data from the database anymore. That’s how we can reduce latency as much as possible and increase our website’s performance by caching all changes made into our database for future usage by our application or client’s requests.

Data storage

Data storage is another way of integrating MongoDB Realm with Woodpecker.co. We can store data into two places. Woodpecker.co database and MongoDB Realm. We used this method for storing structured data such as product data, category data, user data etc., because it doesn’t fit well with unstructured data such as posts and comments. To store data into two places at once, we will use Redis as a bridge between them. Our application will use Woodpecker.co database for unstructured data such as posts and comments, while serverside API will use Redis for structured data such as products, categories and users etc., so that it can be accessed through both APIs – Woodpecker.co (through HTTP. and Java (through JPA. First of all, we will add an event listener into our application to listen for specific events such as adding new products to our database or adding new users etc., so that we will know when they occur and what happened afterwards. Then, we will send a request using Redis to Woodpecker.co’s API to create new products or users into our database, so that all changes made will be tracked as well as cached in our database for future usage by our application or client’s requests. If there are some changes made into our database manually through its interface, we won’t bother sending a request using Redis to Woodpecker.co’s API to create new products or users into our database anymore because we already have them cached in our database through other methods mentioned above (caching. So only when there are changes made into our database through its interface manually, we will send a request using Redis to Woodpecker.co’s API for creating new products or users into our database for future usage by our application or client’s requests (if we actually need them. It is worth mentioning that this approach isn’t working well with unstructured data such as posts and comments since it requires us to store them into two places at once – Woodpecker.co database and MongoDB Realm; therefore it isn’t scalable enough if we have large number of posts per week or month etc., since we would have to spend lots of time managing all of them manually instead of relying on something like an application for doing this task automatically like Woodpecker does (no manual updates required. That’s why it would be better if this approach works only with structured data such as products and categories etc., because it can be scaled up if needed without having any issues regarding tracking all edits made manually or through an application automatically (unlike what has been previously mentioned about unstructured data. However, if you still want to use this approach for unstructured data type like posts and comments too, you can still do so; however, since you may get lots of problems managing all of them manually instead of relying on something like an application for doing this task automatically like Woodpecker does (no manual updates required), it would be better to stick with using this approach only with structured data such as products and categories etc., because it can be scaled up if needed without having any issues regarding tracking all edits made manually or through an application automatically (unlike what has been previously mentioned about unstructured data. This approach works well with post counts too so you can still scale it up if you need to do so; however, since you may get lots of problems managing all of them manually instead of relying on something like an application for doing this task automatically like Woodpecker does (no manual updates required), it would be better to stick with using this approach only with structured data such as products and categories etc., because it can be scaled up if needed without having any issues regarding tracking all edits made manually or through an application automatically (unlike what has been previously mentioned about unstructured data. This is done by creating new products/categories etc., whenever posts or comments are created through posting page or commenting page respectively; thus posts or comments won’t get lost if one day we decide not to use this approach anymore (or if there is no need for using this approach anymore. It is worth mentioning that you don’t have to change any part of your application during this process; however, if you still want to track changes manually instead of relying on something like an application for doing this task automatically like Woodpecker does (no manual updates required), then you can still do so; however, since you may get lots of problems managing all of them manually instead of relying on something like an application for doing this task automatically like Woodpecker does (no manual updates required), it would be better to stick with using this approach only with structured data such as products and categories etc., because it can be scaled up if needed without having any issues regarding tracking all edits made manually or through an application automatically (unlike what has been previously mentioned about unstruct

The process to integrate MongoDB Realm and Woodpecker.co 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.