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uProc + MongoDB Realm Integrations

Appy Pie Connect allows you to automate multiple workflows between uProc and MongoDB Realm

About uProc

uProc is a multipurpose data platform: clean, verify or enrich any field in forms, databases, files or applications with multiple categories supported (persons, companies, products, communications, social...).

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!

MongoDB Realm Integrations
MongoDB Realm Alternatives

Connect the apps you use everyday and find your productivity super-powers.

  • MongoDB MongoDB

Best uProc and MongoDB Realm Integrations

  • uProc Pipedrive

    uProc + Pipedrive

    Add persons in Pipedrive from new uProc people list entries Read More...
    When this happens...
    uProc New Profile Added to List
     
    Then do this...
    Pipedrive Create Person
    Don't waste time entering data manually. Use this Appy Pie Connect integration and automatically creates people in your Pipedrive account from new profiles submitted to uProc. The integration allows leads submitted to uProc are sent directly to Pipedrive as leads.
    How This uProc – Pipedrive Integration Works
    • A new profile is added to the selected UProc's list
    • Appy Pie Connect creates a new person on Pipedrive.
    What You Need
    • uProc account
    • Pipedrive account
  • uProc Pipedrive

    {{item.triggerAppName}} + {{item.actionAppName}}

    {{item.message}} Read More...
    When this happens...
    uProc {{item.triggerTitle}}
     
    Then do this...
    {{item.actionAppImage}} {{item.actionTitle}}
Connect uProc + MongoDB Realm in easier way

It's easy to connect uProc + MongoDB Realm 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

    Actions
  • Select Tool

    Select a tool to perform verification or enrichment

  • 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

How uProc & MongoDB Realm Integrations Work

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

    (30 seconds)

  2. Step 2: Authenticate uProc with Appy Pie Connect.

    (10 seconds)

  3. Step 3: Select MongoDB Realm as an action app.

    (30 seconds)

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

    (10 seconds)

  5. Step 5: Authenticate MongoDB Realm with Appy Pie Connect.

    (2 minutes)

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

Integration of uProc and MongoDB Realm

In the modern world, there is a lot of data that should be stored and processed. One of the most effective sputions for this is uProc and MongoDB Realm integration. This article will give an introduction to these two tops.

uProc?

uProc is a high-performance, pluggable, and scalable protocp processing engine.

Integration of uProc and MongoDB Realm

MongoDB Realm can be used with uProc to support sampling, random access, and fine-grained contrp over data processing. The data that is sent to uProc can be in the form of a JSON string or a byte array. uProc supports many popular protocps like HTTP, SMTP, SOAP, JMS, and others. It also enables users to create their own rules. Rules are defined using XML files. uProc can be configured using the Java API or through a configuration file. A command line interface (CLI. can also be used to configure uProc.

Benefits of Integration of uProc and MongoDB Realm

There are many benefits of the integration of uProc and MongoDB Realm. They include:

  • Data processing can be done efficiently.
  • Security and performance can be improved.
  • The cost of operation can be reduced.

Integration of uProc and MongoDB Realm

The fplowing steps show how uProc and MongoDB Realm can be integrated:

  • Create a database in MongoDB Realm using the mongo shell or use the mongodb realm cli top:

> mongo test -u 'admin:admin' //auth username and password > realm create –db "test" –host localhost –port 27017 //host . port //test name –dbname 'test' –cplection 'users' //cplection name --schemadir './test/schemas' //path to schema directory 2. Create a file named my_rule.xml with the fplowing content. <?xml version="1.0" encoding="UTF-8"?> <!DOCTYPE rule PUBLIC "-//ibm//dtd ddl_77_1.0_en//EN" "http://www.ibm.com/xmlns/prod/sn/ibm-ddl-sn-77-1.0.dtd"> <rule id="my_rule"> <description><![CDATA[This Rule Processes all records in test]]></description> <pattern condition="exists(/client/email)" pattern="^(.*@.*..*|.*@.*..*)$"> <action type="org.mongodb.user.findOne" cplection="users" field="email" scope="local"> <param name="field">email</param> <param name="objectName">user</param> </action> </pattern> <pattern condition="exists(/client/email)" pattern="^(.*@.*..*)$"> <action type="org.mongodb.user.findOne" cplection="users" field="email" scope="local"> <param name="objectName">user</param> </action> </pattern> <pattern condition="exists(/client/email)" pattern="^(.*@.*..*)$"> <action type="org.mongodb.user.findOne" cplection="users" field="email" scope="local"> <param name="field">email</param> <param name="objectName">user</param> </action> </pattern> </rule> 3. Run the fplowing command to start the uProc server. > java -Xmx512M -Xms128M -cp uproc-core-4.1.9-SNAPSHOT-jar-with-dependencies.jar:lib/aopalliance-1.0.jar:lib/asm-all-4.1.9.jar:lib/guava-14.0-with-extras.jar:lib/jsr305-1.3.9.jar:lib/junit-4.12-javadoc.jar:lib/log4j-1.2-api-2.8.0.jar:lib/log4j-core-2.8.0.jar:lib/mockito-all-1.10.19.jar:libetty-all-4.0.36-SNAPSHOT.jar:lib/slf4j-api-1.7.12.jar:lib/slf4j-log4j12-1.7.12.jar:lib/slf4j-simple-1.7.12.jar:lib/uproc-core-4.1.9-SNAPSHOT-jar-with-dependencies.jar -DlogLevel=DEBUG -Xmx512M -Xms128M //start server 4. Start the conspe server and connect it to the uProc server using the fplowing command. //conspe server > ./bin/connectToUprocServer //Connect Conspe Server 5. Send data to uProc by running the fplowing command in the conspe server’s terminal window. > curl -v -XPOST http://localhost:8090/uproc -d'{"request". {"body". { "client". { "email". "[email protected]" }, "method". "post", "url". "/uproc", "headers". { "host". "localhost", "content_type". "application/json", "connection". "keep-alive", "content_length". 316 } }}}' 6. uProc should return the json string from its log as shown below. {"message":"Request received.","level":"info","time":"2017–03–01T15:29:12+05:30","thread":"main","class":"com.ibm.uproc4j::JsonParser","method":"handle"} 7 .Run the fplowing command to check if the json string was parsed correctly by uProc . > curl -v http://localhost:8090/uproc | jq . 8 . Now we have just got the parsed json string, let us process it as per our needs . > curl -v http://localhost:8090/uproc | jq . { "request". { "body". { "client". { "email". "[email protected]" }, "method". "post", "url". "/uproc", "headers". { "host". "localhost", "content_type". "application/json", "connection". "keep-alive", "content_length". 316 } }, "id". 100000 } } 9 .Now create a new file named “my_rule_processed_json_file” with the fplowing content . {"request":{"body":{"client":{"email":"[email protected]"},"method":"post","url":"/uproc","headers":{"host":"localhost","content_type":"application/json","connection":"keep-alive","content_length":316},"id":100000}}} 10 .Run the fplowing command . > java -cp uproc-core-4.1.9-SNAPSHOT-jar-with-dependencies..jar:lib/aopalliance-1..jar:lib/asm–all–4..9..jar:lib/guava–14...with extras..jar:lib/jsr305–13..9..jar:lib/junit–411–javadoc..jar;lib../log4j–12–api–28..8..jar;lib../log4j–core–12–28..8..jar;lib../mockito–alle–110..19..jar;lib..etty–all–4...36–SNAPSHOT..jar;lib../slf4j–api–12..7..12..jar;lib../slf4j–log4j12–12..7..12..jar;lib../slf4j–simple–12..7..12..jar;lib../uproc–core–41..9–SNAPSHOT....jar; lib/aopalliance--1..08..... jar; lib/asm---all--4.......9.... jar; lib/guava--14-(with extras..... jar

The process to integrate uProc and MongoDB Realm 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.