You need data integration for simplified data analytics. Given how siloed data sources have gotten with the evolution of the modern data stack, it’s become even more important to bring data from multiple disparate sources to a central repository.
Now, there are various methods to execute data integration between two applications. Point to point data integration, ESB integration, middleware integration, and cloud data integration, to name a few.
Cloud data integration has been picking up a lot of steam in the last decade, and according to Gartner analysts, more than 85% of organizations  will embrace a cloud-first principle in 2025.
In this article, we’ll be talking about the differences between Point to point data integration and cloud data integration.
What is Point to Point Data Integration?
P2P Integration (Point to Point Data Integration) involves connecting two applications through a hand-coded connector. Using this approach, data is transferred directly from one application to another via a direct connection, like a web service or an API.
In the past, in-flight data transformations had to be executed as data moved from one place to another. This meant data teams had to manually code their data pipelines with specific transformations. Before the widespread adoption of SQL, these transformations had to be written in a different language (Java/Python), which led to the development of point to point data integrations; along with the creation of complex pipelines between systems.
However, point to point data integrations were limited to a single source and destination, which meant that the teams couldn’t use or access all of their customer data.
With the increasing number of data sources, more alternatives popped up in the market. For example, cloud data integration.
What is Cloud Data Integration?
According to a recent survey by the Enterprise Strategy Group. 85% of organizations indicated that they deploy applications on two or more IaaS providers, which means that more and more people are adopting a multi-cloud approach. Performance flexibility (35%) tends to be the number one reason behind the increased adoption of the multi-cloud approach. This indicates that there is a growing need to integrate previously siloed cloud systems.
Cloud integration tools provide you with prepackaged or easily configurable integration flows aimed at helping non-IT business users build pipelines without help from developers. Here, companies tend to outsource some or all of their integration needs to a service provider.
Integration service providers, like Hevo, provide detailed end-to-end integration implementation services.
Why do Data Teams use Point to Point Data Integration?
- Data teams might use point to point data integration when they’re trying to implement an application-centric integration design.
- For short-term projects that don’t need long-term investment in expensive integration technology, point to point data integration might be the way to go.
- Data teams that want a higher degree of customizability and control over their integrations might opt for point to point data integrations.
Cons of Point-to-Point Integration
- Increasing Complexity of Dependencies: When you connect applications using point to point data integration, you create a dependency between them. Say, for instance, you’ve integrated App A and App B. When App A is updated or modified, you’ll have to change the integration that connects it to App B. You’ll also have to test the integration again to make sure it’s working properly. If you add more apps to the mix, the setup gets more complicated. Therefore, this limitation doesn’t make point to point data integration a suitable fit if you’re looking to scale.
- Difficult to Track: Since there is no centralized system in place for Point to Point data integrations, a large chunk of your team might be in the dark about the details of these integrations. This could make it difficult to monitor your network of integrations and troubleshoot them over time. Plus, your custom-built P2P integrations usually lack the reporting capabilities that tell you what is happening between systems. This makes debugging problems, performance measurement, etc. a nightmare.
- Implementation is Time-consuming: Setting up a single point to point data integration takes up a large chunk of your dev team’s bandwidth, leaving less time for them to focus on other needs of the stakeholders and the organization.
- Not Future-proof: The applications that you want and the way you want them to interact will change with the evolution of your business. As the number of applications in your tech stack increases, the chances of your point to point data integration system becoming a single point of failure in your network increase as well. It is pivotal to reduce the number of ‘single points of failure’ for integration, but a point to point data integration approach makes it difficult to eliminate the bottlenecks in the system due to its high degree of coupling.
Why do Data Teams use Cloud Data Integration?
Cloud data integration lets you deploy and adapt new integration patterns faster to keep up with market changes. With cloud data integration, you can connect quickly to both cloud applications and on-premise data sources to seamlessly integrate high volumes of data.
Cloud data integration tools happen to cover a wide range of mobile and cloud-based endpoints. For instance, spreadsheets, CRM applications, ERP applications, digital marketing, digital visualization, project planning, file sharing, to name a few.
How does Cloud Data Integration overcome the limitations of P2P Integration?
Let’s take the example of a cloud data integration tool, Hevo, and illustrate how Hevo can overcome the limitations we listed in the previous section:
- Better Visibility: Unlike P2P solutions where lack of central governance makes it difficult to see who has access to data, a cloud data integration tool like Hevo provides complete control and visibility over your data while helping you minimize costs. Along with this, Hevo also provides you with alerts about your pipelines, data ingestion, activation status, or any activity that needs your attention, through third-party applications like PagerDuty or OpsGenie; or email.
- Better Scalability: We’ve talked about how with more applications it becomes increasingly more complex to handle P2P integrations, making it unsuitable for companies that are looking to scale up their tech stack. For these companies, a tool like Hevo would be the perfect solution. Hevo’s multi-tenant platform uses various components of Amazon’s AWS cloud for its infrastructure. The platform is designed to process billions of records and can automatically scale up or down based on the needs of your workload. Hevo’s architecture ensures the optimum usage of system resources so that you can get the best ROI.
- Intuitive Interface: You need considerable technical expertise to build and maintain point-to-point integrations. On the other hand, Hevo’s intuitive user interface makes it easy for both technical and non-technical users to set up and manage data pipelines. But that’s not all. Hevo’s design approach goes beyond data pipelines. Its analyst-friendly data transformation features are well integrated into the platform to streamline the analytics tasks. Also, since you’re allowing the employees who consistently use the apps to implement the pipelines, they’re much more likely to build pipelines that do a better job of addressing their team’s needs.
- Fully Managed: Unlike P2P integrations where you need considerable bandwidth of your dev team to keep it running smoothly, with Hevo you can use that bandwidth for more productive tasks. Hevo takes away the tedious task of schema management and automatically detects the schema of incoming data and maps it to the destination schema.
You can take Hevo’s 14-day free trial to see for yourself if it’s a good fit for your needs.
Other Key Alternatives to P2P Integration
Middleware is a software that serves as the middleman between two or more systems to allow them to communicate with each other. It bridges diverse tools, technologies, and databases so that you can integrate them into a single system. The single system can then offer a unified service to its users.
Middleware can typically establish a secure connection while managing traffic across distributed systems. It’ll hide the complexity of the underlying operating system and network to simplify the integration of legacy and new systems.
Here are some scenarios where Middleware is a good option:
- For enterprise-level organizations due to higher internal team requirements and costs.
- If you’re scaling at a rapid pace, middleware is recommended because of its scalability and centralized management.
- You also need to keep the complexity of your data integrations in mind. P2P integration is a good choice for simple setups. Middleware can efficiently handle multiple connections and is a good fit for more complex integration requirements.
- If consistency is a matter of concern for you, you might want to opt for middleware for your workflow. That’s because it provides standardized data mapping for consistency. P2P integration adopts a manual data mapping approach which might lead to inconsistencies.
IPaaS is a hub-and-spoke approach and is a subset of Middleware Integration. However, there is one key distinction between the two. Middleware integration requires highly experienced integration experts, while IPaaS platforms use simplified UX/UI design that allows even non-developers to manage their integrations.
IPaaS (Integration Platform-as-a-Service) provides the following benefits over Point-to-Point Integration:
- Ease: One of the pivotal advantages of IPaaS over Point-to-Point integration is the ease of maintenance and deployment. Instead of spending all your team’s bandwidth to monitor point-to-point connections, you can use IPaaS to free that bandwidth for more productive tasks.
- Costs: Similar to most SaaS applications, an IPaaS is a subscription service with pricing that’s based on the customer’s needs. The service tiers for IPaaS solutions are usually based on the number of connectors available, connections required, and access to advanced features. Pricing is often straightforward and can be found on the website of the service provider. Unlike P2P applications, IPaaS solutions are free from the high costs involved in maintenance and setup.
- Integration options: With IPaaS solutions you aren’t limited to cloud-to-cloud integrations. You can easily integrate between on-premise and cloud systems. You might need to install agent software behind the corporate firewall for smooth execution for this scenario. IPaaS will include connectors to all different kinds of SaaS, text files, protocols like ODBC, and databases.
- Up-to-date Connectors: The IPaaS vendor keeps the connectors up-to-date, keeping up with the upgrades rolled out by respective SaaS companies. They’ll also test the new versions and implement changes wherever necessary. This means you can say goodbye to the endless regression-test cycle of point-to-point integration.
IPaaS is a good fit for the following situations:
- You want to outsource the operational aspects of your integration middleware.
- Your tool stack is migrating to the cloud.
- If you’re struggling to integrate new types of data stores or cloud applications, platforms, connected ecosystems, etc. IPaaS is perfect for meeting these needs for which project requirements are frequently changing. This means a faster time to value is a crucial requirement.
- If you have a bare-bones integration setup or are starting from scratch, IPaaS may be a good option to ensure flexibility and future-proofing.
In P2P Integration, the two systems are tightly coupled, which means it is more suitable for workflows that have a small number of applications. But as the number of tight couplings grows, the infrastructure becomes more difficult to maintain.
As a more flexible approach to application integration, ESB uses a hub-and-spoke approach. The integration application will serve as the hub with spokes connecting to the respective applications.
Every ESB usually has these two components:
- Centralized Monitoring and Administration: Here, you’ll get a view of the transactional flows of performance of interactions that take place inside ESB.
- Service Registry: All the services exposed to the ESB are registered and published here. It also acts as a point of discovery for anyone who wants to use those services.
The IT staff within an organization builds connections between applications and ESB, while the staff members code the transformation and other integration tasks that you need.
ESB is the right choice for you in the following scenarios:
- You have a large portfolio of integrations to manage.
- You want centralized control of access to all services through application services governance.
- You want to create composite applications or expose composite services that collect data from different API management systems, systems of record, or ESB technology.
- You’re planning on changing or transforming the data being passed between the applications to make the integration work.
- You want to modernize applications or execute a business transformation that’ll require the bandwidth of existing applications using APIs and service-oriented architecture (SOA).
There are multiple ways to execute data integration between two systems. In this article, we’ve gone over the key differences between two such methods: Point to Point Data Integration and Cloud Data Integration.
If you’re in the market for a real-time data replication tool, try Hevo. Hevo Data can also help you set up a near-real-time data transfer pipeline between any two platforms. With an intuitive interface and data transformation capabilities, Hevo is an effective solution for your data integration needs.
If you don’t want SaaS tools with unclear pricing that burn a hole in your pocket, opt for a tool that offers a simple, transparent pricing model. Hevo has 3 usage-based pricing plans starting with a free tier, where you can ingest up to 1 million records.
Schedule a demo to see if Hevo would be a good fit for you, today!