The SnapLogic Platform accelerates digital transformation across the enterprise and empowers everyone to integrate faster and easier with Generative AI-led integration. Whether you are automating business processes, democratizing data, or delivering digital products and services, SnapLogic enables you to simplify your technology stack and take your enterprise further by solving the fundamental app & data integration issues. Thousands of enterprises around the globe rely on SnapLogic to integrate, automate and orchestrate the flow of data across their business in a low-code environment. SnapLogic also provides a flexible AI architecture that enable customers to leverage current & future GenAI solutions to develop generative AI applications faster while controlling costs. SnapLogic not only helps organizations with app & data integration but consequently allows organizations to focus solely on creating complete GenAI applications without data science expertise.
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I like the graphical elements and the options available in each level of the service. There really is no stone left unturned by Snaplogic - if you need it, it probably exists in some form or another. And the orchestration side of the business is not only functional, but sort of inspiring. It generates a lot of ideas for not only how to use the service, but how to change our own services to work more closely with SnapLogic. The setup and deployment of the processing engines for SnapLogic is incredible and a huge selling point - the fact that we can process all requests through our own containers is amazing and we can tailor that experience to our services and our customers.
Easy to try things. Direct output
It can facilitate very quick time to production from initial conception to the point where you can rapidly build something simple on a call with a stakeholder as a demonstration. With over 1000 connectors, you can connect almost anything to anything. The design of a pipeline is very visual, and to developers, its almost self-documenting, this coupled with the additional features of SnapGPT for documenting pipelines in more detail allows for a faster and consistent throughput. As for the service, support response times are very fast, with additional interest from success managers on regular calls ensuring we are getting the best service.
The separation between the design interface and the management or monitoring interface can be confusing and tough to navigate. I have to keep multiple tabs open in my browser to keep the different interfaces open all at once since the transition between them takes time and doesn't allow a very clear path to get back to a certain state. I understand that these are complex web applications that are engineered separately from each other, but Conway could almost draw an org chart of the company based on how the different interfaces are designed and how they work together. There's one other very specific spot that always trips me up - when looking at a task there is a click that will open the task and let me edit it, but there's another click that gets me to the implementation of that task - very important details about how to address that task from my own app, and I always end up clicking the wrong thing and having to backtrack. This interface is the hardware equivalent of a USB-A plug - no matter how certain I am that I'm plugging it in correctly, I almost always end up having to try again and again. Lastly, the groundplex setup was not as straightforward as I would have liked it to be. In addition to all the technical documentation that we read to get those set up, we have multiple pages in our internal documentation service that are dedicated to this topic. I feel like those documents get stale really fast, and as new features are rolled out, the versioning often breaks our procedures. All of these dislikes are definitely nitpicks, and not key to our decision making about integration partners.
The limitations of drag-n-drop. Support is quite poor when faced problems. Outsourced support who don't communicate well.
The main issue that pops up from time to time is around capacity planning and maintaining/restarting nodes, there isn't a native way to easily see a holistic view of all of your future scheduling, I built something in python which utilizes the schedule metadata as a work around. While SnapGPT often gets you out of a tricky spot with complex coding, I find that the answers that it gives often include hallucinated functions, and it can get stuck in a loop of correction and hallucination. I don't have anything in this field to comment on regarding the service, as it always meets or exceeds my expectations.