Common Features Across The Competitor Landscape

The team has been meeting in Grenoble, France, reviewing the roadmap, and planning for the rest of 2018. Part of this exercise is looking at the common features offered by our competitors, which includes the leading cloud platforms AWS, Azure, and Google. We enjoy learning from the competition, and learning what features they offer, helping us better understand what their customers need, which helps us think more deeply about how we should be shaping our services in the future. One part of this competitor landscape feature analysis is being realistic about what we want to include in the roadmap vs what we’d rather partner with another company to deliver. We are very interested in being the best at what we do, and are very pragmatic about how we expand our roadmap. With this in mind, here are the features we’ve identified as part of work, and have been discussing as part of our road map, as well as our partnerships with other service providers in the space:

Storage – Storing data from streams in data lakes, and other common database and storage solutions.competitor landscape
Playback – Allow streams to be played back, showing previous stages of the streams for a variety of time frames.
Time Series – Providing time series of historical data to be delivered as playable streams.
Query Language – Offering a query language on top of streams which users can craft custom query templates that dictate the flow of informatin.
Rules & Filtering – Providing the ability to setup filtering rules that exclude and refine the data streams.
Analysis – Allow for the analysis of data that is flowing through streams in real time, as well as historical evaluation.
Machine Learning – The training of machine learning models using data streams, that allow models to be incrementally updated.
Blockchain – Allow data, analysis, and other elements of the data streams to be stored in the blockchain.
Offline / Sync – Allow for offline data to be accessed when streams are disconnected or interrupted for a variety of reasons.
Network Optimization – Allow for streams to be optimized and adjusted depending on the network they are be transmitted on.

There are other features on our list, but these are the recurring features that have come up several times during our discussions. Representing the common things people are wanting to do in parallel with delivering streams of data, and evolving their API infrastructure to be more event-driven. Reflecting the common requests we hear from customers, and assume our competitors are hearing as well, as they work to expand the features they bring to the table.

Before adding anything to our road map, we spend a good deal of time understanding how the API Gallery can be used to deliver this functionality, and how we can partner to bring these features to the table. This process helps us keep our road map lean, meaningful, and doing one thing well–delivering real time streams of data, and optimizing existing API infrastructure to be more event-driven. Allowing API providers to optimize their platforms to meet the next generation of demands from the partners, integrators, and consumers.

AI in Finance White paper - competitive landscape

**Original source: blog