Best Salesforce Integration Patterns — AppShark

Avril Payne
5 min readFeb 4, 2021

150,000Source : IDC, Worldwide Semiannual Software Tracker, October 2020. + customers — from small businesses to FORTUNE 500 companies — are growing their businesses on Salesforce owing to its secure, scalable nature and having a suite of world class-leading applications for sales, service, commerce, marketing, and more.”

Also Read: Transform Business with Salesforce SAP Integration

Salesforce and its suite of CRM based applications have improved marketing and sales operations of enterprises by offering innovative products and services that cater to customers’ needs. Implementation of Salesforce helps increase and accelerate sales, enhance marketing capabilities and help advance customer loyalty by giving teams’ access to updated customer information. Now this access can further be used to streamline business processes and create effective services and solutions. To obtain the best out of this dynamic platform, it is essential to integrate it with other necessary enterprise systems and third party applications within the business. By adopting the right Salesforce integration pattern and strategy businesses will get greater operational visibility, seamless data flows, unlock new opportunities and add value to their customers.

Top five patterns for Salesforce Integration

All of these integration design patterns serve as a road-map for integration specialists, who can leverage them accurately to connect data, applications, systems and devices within the business. These patterns are the most logical sequence of steps to execute a specific type of Salesforce integration that has been established from actual use cases.

To set up a template for Salesforce integration, clarity on best practices and patterns is necessary. This would help them be reusable as a reference in the future. The pattern must contain a combination of at least two of the below basic elements:

  • The source system which houses data prior to execution of integration.
  • The criteria determining the scope of data to be copied, moved or replicated.
  • The kind of transformation data sets will be undergoing in this process.
  • The final destination system where data will be inserted.
  • The results which capture and compare the original state with the desired state.

Based on the above conditions, let us now look at the top common Salesforce integration patterns.

  • Moving a specific set of data from a particular point in time from one system to another.
  • Developers can build automation services to create functionality across numerous teams.
  • This pattern is appropriate for multiple integration use cases or on need-basis via an API.
  • Helps save a great deal of time for development and operations to create reusable services for frequent data migrations.
  • Ideal to handle large volumes of data, processing batch records etc.
  • Critical to keep enterprise data agnostic from tools used to create, view and manage it without data loss.
  • Moves data across a single source system to multiple destination systems (ongoing, near real-time or real-time basis).
  • One-way synchronization from one to many.
  • Transactional and is optimized for quick processing of records .
  • Up to date data is shared between multiple systems across time.
  • Highly reliable and helps avoid losing critical data in transit as exchange is usually initiated in mission-critical systems by a push notification or are scheduled.
  • Allows for immediate transfer of customer data between systems; for e.g.- an action in Salesforce to immediately translate can initiate order fulfillment processing.
  • Common use cases include: creating a sales order in SAP when an opportunity is marked as CLOSED or WON in Salesforce, or synchronizing real-time data from say Siebel to Salesforce.


  • Takes or receives data from multiple systems, copies /moves it into one system.
  • Removes the need for multiple migrations on a regular basis, eliminating concerns about data accuracy and synchronization.
  • Simply strategy of extracting and processing data from multiple systems into a single application or report.
  • Easy to query multiple systems on demand and merge data sets to create or store reports.
  • Contains a custom logic that can be modified to merge and format data as needed and which can be easily extended to insert data into multiple systems, such as Salesforce, SAP and Siebel.
  • Some uses — Updating Salesforce with data from both ERP and issue tracking systems, creating a dashboard that pulls data from multiple Salesforce instances, or building APIs that collect and return data from multiple systems, or that report across multiple systems.
  • Enables extraction and processing of data from multiple systems and merging them into one application( data is always up to date, does not get replicated, and can be processed to obtain any desired dataset or report.
  • Some key considerations include collecting data, the scope of the source data and insert data, merging multiple datasets, formatting data, and any additional destinations.
  • Combining multiple datasets needs consideration of how to merge them and how to present the data in the final report or destination system.

Bi directional sync

  • Unites multiple datasets in multiple different systems, causing them to behave as one system with different datasets.
  • Comes in handy when different tools or different systems need to accomplish different functions in the same data set.
  • Enables both systems to be used and maintains a consistent real-time view of the data across systems.
  • Enables the systems to perform optimally while maintaining data integrity across both synchronized systems.
  • It can modularly add and remove two or more systems that subspecialize inside a domain as storage.
  • Advantageous when object representations of reality have to be comprehensive and consistent.
  • Some use cases -integrating Salesforce with multiple systems that contribute to operational efficiencies and a streamlined quote to cash but still serve as the system of record for all data that needs to be synchronized.


  • Singles out intersection of two data sets and does a bi-directional synchronization of that scoped dataset, if that item occurs in both systems naturally.
  • Creates new records if they are found in one system and not the other. And agnostically synchronize objects as long as they are found in both systems.
  • Useful for cases in which two groups or systems only want to share data, but only if they both have records for the same items or contacts in reality. For example, hospitals might want to sync patient data for shared patients across hospitals, but want to avoid related privacy violations.
  • Important to define the term “same” across records which may vary from industry to industry -in the retail industry, while targeting offers to customers, the same name may be close enough to achieve the goal; in healthcare relying on a name alone could have serious consequences if two patients have the same name and different courses of treatment .

Integrating Salesforce with third party applications is inevitable; businesses might often find themselves in need of expertise and experience of the right Salesforce consultant and service provider for such Salesforce projects

About AppShark

AppShark is a Salesforce Gold Certified Partner based in Dallas, Texas. Our expertise which includes Salesforce Integration, Implementation customization, set up, and configuration — has been perfected through the many years served in the Salesforce industry. We also provide software integration services including strategy, development, and management to enable a continual flow of information from the cloud, premise to premise, or from cloud to premise platforms.

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Originally published at on February 4, 2021.



Avril Payne

Marketing Specialist at AppShark Software Solutions