Amazon Tensor Flow vs. OutSystems

A well-suited scenario for using AWS Tensor Flow is when having a project with a geographically dispersed team, a client overseas and large data to use for training. AWS Tensor Flow is less appropriate when working for clients in regions where it hasn't been allowed yet for use. Since smaller clients are in regions where AWS Tensor Flow hasn't been allowed for use, and those clients traditionally don't have enough hardware, this situation deters a wider use of the tool.

Incentivized

Well suited for internal exposure of business processes (invoicing, API layer to other systems, customer maintenance etc), whether a UI is required or not. Not so well suited for full fledged web design. An OutSystems application must serve one particular business need, if gets too much functionalities and responsibilities it tends to get chaotic and complex.

Incentivized

• Amazon Elastic Compute Cloud (EC2) allows resizable compute capacity in the cloud, providing the necessary elasticity to provide services for both, small and medium-sized businesses.
• Tensor Flow allows us to train our models much faster than in our on-premise equipment.
• Most of the pre-trained models are easy to adapt to our clients' needs.

Incentivized

• Developing end user interfaces with ease and speed with a modern look and feel.
• First class low code development to reduce time to market with visual programming
• Their technical support team is fast and responsive. We've yet to have any issues they could not resolve.

Incentivized

• SageMaker isn't available in all regions. This is complicated for some clients overseas.
• For larger instances, when using a GPU, it takes a while to talk to a customer service representative to ask for a limit increase. Given this, it's recommendable to ask in advance for a limit increase in more expensive and larger cases; otherwise, SageMaker will set the limit to zero by default.
• Since the data has to be stored in S3 and copied to training, it doesn't allow to test and debug locally. Therefore, we have to wait a lot to check everything after every trail.

Incentivized

• Price – The licensing model of OutSystems is very expensive and not suitable for small scale developments. This is offset by the time to develop and stability for larger scale developments
• Flexibility on PaaS version – The PaaS hosted version of OutSystems limits your flexibility to access the front end and backend database systems which can significantly restrict your options on high data volume developments or where anything requiring slightly out of the ordinary access is required
• Same price for PaaS and self-hosted system. Licensing model dictates that you pay the same price even when you host the system on your own hardware which effectively means you pay more to manage the infrastructure yourself

Incentivized

We are very happy with OutSystems and our developers deliver good work. OutSystems lets us build new software on a regulare (2 weekly) basis, which is highly flexible and adjustable. Even without very much experience, our developers manage to build usefull software, which is working a lot better than our previous (legacy) software.

OutSystems has a feature in which we can develop a functionality in a application and can use that functionality in another application without developing it again. That is main plus point for the development team so they can work with different functionalities rather focusing on the same thing again and again. if we want to make any change on the user side then we can make it live with just the deployment using the service center.

Incentivized

The tech support is very reachable. Usually by [email] from but also by phone if needed. We had some difficulties at the start with understanding "what our machine was doing" under high performance load. After some good sessions understanding our needs they delivered good solutions for our problems we had in the beginning.

Excellent material full of hands on that improve the understanding of the platform.

The online training material is well designed and explanations are step by step, helping trainees to understand and follow each exercise and new concept.

In a large company, patiently and consistently work the behind the scenes politics with business and IT partners across the firm.
This is transformational - you will need a solid set of key business partners to lock arms together to move forward.

Incentivized

Microsoft Azure is better than Amazon Tensor Flow because it provides easier and pre-built capabilities such as Anomaly Detection, Recommendation, and Ranking. AWS is better than IBM Watson ML Studio because it has direct and prebuilt clustering capabilities AWS, like IBM Watson ML Studio, has powerful built-in algorithms, providing a stronger platform when comparing it with MS Azure ML Services and Google ML Engine.

Incentivized

I tried to use WordPress with some success. Also looked at Joomla. But when I saw OutSystems I knew I had been wasting my time there. It takes you longer to get going with OutSystems - but even I as a novice realized immediately that Outsystems is simply in another league. Outsystems is powerful. (Can you compare WordPress and Joomla to Outsystems - I don't think so).

• Positive: It has allowed us to work with our overseas teams without any large hardware investing.
• Positive: Pre-trained models significantly reduce the time to develop solutions for our clients.
• Negative: Since it's a relatively new tool, you have to be careful about not paying for large errors while learning to use the tool.

Incentivized

• The ease of use of the OutSystems development process has been the biggest ROI for us. We have developed our Framework product and maintained/enhanced it with only 4 workers.
• OutSystems has enhanced their product very significantly over the last 4 years. They have gone from a simple to use tool to a very simple to use sophisticated tool that covers the standard mainframe-based computing apps and the apps used on handheld mobile devices all using the same basic set of development tools.

Incentivized