An iPaas (integration platform as a service), integrates systems, dbs and warehouses. Typically, they come with connectors, transformers and sdks to move data between your services. Their main feature, is configuration over development. You might think, why would I need an iPaas?
Well, read on....
Symptoms which show you need an iPaas
You have a data engineering problem but don't know it yet
Business intelligence and data aggregation seemed like a solved problem.
We push data onto streams, queues and staging databases, and then someone else aggregates it and produces a report for someone upstairs.
But.... It's always broken, our initiatives are expensive, and we can't seem to do anything quickly. Everything is custom-built, there is no coherence because there is no need.
The business is really keen to use Anaplan, ChatGPT, Salesforce, Tableau, PowerBI, CX tools etc. but it's going to take us months to build these integrations.
That is a data engineering problem.
Organisations that struggle with integrations, ELT and heavy developer costs for seemingly mundane integrations are in an ideal place to benefit from an iPaas.
You have a data-mush
Contrary to a data mesh, a data mush is a mixture of FTP, REST, gRPC, Bash, PL/SQL that stinks up your infrastructure. These glorious totems of long-departed developers create a complexity that few understand. When a change needs to happen or something breaks, all hell lets loose as there is little change control, less reporting and often a poor perception of technology departments by senior leadership.
Replacing all these jobs and integrations will be a hellish job. You've created a technical debt data mush.
Why an iPaas will help
Today, the promise of the iPaas is to unify, analyse and activate customer data, and to break down traditional data, technology and channel silos within an organisation. The platform that was predominantly adopted by marketing teams for targeting and engaging with audiences is now expanded to the entire customer journey, from first touch to post sales.
Rather than teams having to manage dozens of data silos that exist in each of their applications, CRM, or primary user data stores, the iPaas can unify that data, help teams slice and dice audiences, enrich customer profiles, and paint an overall customer profile for the business team to act upon.
Players in the space we like
Customer Data Platform with nice SDKs and range of integrations.
Open source with some caveats and features restricted.
Marketing focused and more likely to suit those who choose to send their data to a cloud Saas offering.
Not a great for companies looking to run in their own clusters.
ETL and ELT focused services.
Huge number of integrations.
Good documentation and support.
Key management and security can be tricky.
Designed to be a low-code integrator platform but occasionally lacking enterprise capabilities.
Jack-of-all trades approach has some downsides as large data volumes often leads to complaints on their support forums.
Early stage Enterprise iPaas.
Looks like it will be focused on security and Enterprise microservice architectures.
Go and kubernetes native which is always a plus.
Some learning curve require to get the initial project going.
Focus is on Enterprise services.
Kubernetes native (which we love).
Low-level event mapping.
Not a whole pile of Saas integrations.
Maintenance and roadmap is somewhat vague.
An iPaas is a great option to cut down integration time and introduce agility to your data organisation. This field is destined to grow and new players will emerge. Companies have proliferated and raised substantial amounts of capital. While the benefits of these products are clear- i.e. more reliable data pipelines and better collaboration - adoption is still relatively early, as customers discover relevant use cases and budgets.
The future is low-cost integration between services so we recommend having these products on your discovery roadmap soon.