Why gamble on building your own data streaming solution?
Cloud computing began as a massive, scalable IT system, and it has never stopped since then. Cloud computing has changed the way we consume software. The use of cloud-based solutions as well as the integration of services are the most recent methods of developing and using software and data solutions.
There is no doubt that the company’s engineering team will develop the CRM that best suits its needs. Would you consider doing this instead of using Salesforce or Hubspot? Do you even have a development team to handle such a project? The cloud revolution has not only changed the way we obtain software (build versus buy), but it has also led to the evolution of products based on the needs of thousands of clients, not just your own.
Self-built solutions vs. cloud solutions become important and have significant implications only when dealing with problems of high complexity. With a simple problem, margins tend to be small, as do the arguments.
The nature of streaming data makes data streaming solutions complex. Streaming data has a very high entry point which is not related to your use case and engineering capacity — it starts big and grows rapidly, never stops flowing, has irregular flux, order and arrival times.
It is common for streaming solutions to involve massive integration projects of multiple software packages for ingestion, processing, reliability, state, and delivery. A project of this size has engineering considerations, but the scale of integration adds to the complexity.
The brutal fact of these projects is that they only start when they end.
Building and maintaining a reliable, secure, and scalable streaming infrastructure in-house comes with significant costs and burdens — ones that only grow over time. Capacity needs to be planned, clusters sized and rebalanced, failover and scaling processes designed. The paradox is that the more use cases optimized your initial solution was, the more likely the chances you had to keep developing and adapting it, due to use case evolution, by investing more and more resources.
That is the moment of truth. The point at which you place your bet on the future of your company’s data strategy and resources. A modern organization who wants to be elevated by real-time data without the long lasting burden of managing a complex data infrastructure OR an old style NIH organization optimizing the moment only to be sinked by the cost of its decision.
A fair statement would be that the bet is between having or losing control, optimization, customization and even tech-edge. But as true as these arguments may be, does your company have the capacity to keep those advantages for long?Are they really necessary? Isn’t it more likely that a “one-fits-all service” would be best shaped by the forces of the market, giving the one who chose it early an advantage in the long run?
The truth is that very few companies require a streaming data infrastructure of their own. In many cases, companies who build their solutions lose flexibility due to their inclination to change something that has already been invested a great deal of time and effort into. The companies that use an as-a-service solution do not share this mindset. With the advent of cloud computing, the concept of infrastructure as something you do not need to change has been revolutionized.
The bottom line can be estimated based on Forrester research commissioned by Confluent, which shows a return on investment exceeding 250% for switching from self-managed Kafka to the Confluent cloud. In order to achieve a full or end-to-end streaming data solution, at least three solutions will be required (data ingestion, processing, and orchestration) with ongoing investments in code development for integration. The total savings for the full or end-to-end streaming data solution over time will be enormous.
So, “Place your final bets.”
