eql

r development and production environments must match. * Be ready to onboard new team members. "Works on my laptop" is never acceptable. Enough of our application must be documented and automated so that anyone with a technical background "reasonably proficient" in our work can contribute without requiring hand-holding. Or course, we'd never turn down a request for help. Our requirements are: * Clojure, Clojurescript, and Datomic are immutable choices. We love these solutions for their simplicity and expressiveness. We believe these are the best choices available for achieving our long-term business goals. * Be measurable. Our work should be guided by data not guesswork. * Be testable. The entire application should have 100% test coverage as measured by its acceptance or integration tests (not unit tests). Changes should be made with confidence. * Be performant. As builders of both the front-end and back-end components, we should encourage cooperation between them, not purposefully isolate them. Our customers and the end-user experience should be our priorities, not artificial divisions between software components or technical teams. Each component of the application should cooperate to support progressive enhancement where every URL is a real URL that, when requested, returns a server-side rendered page view. Further actions by the user result in browser-side changes through API calls and minimal component updates. * Be pragmatic. We should be eager to innovate when the need arises. However, we should be humble enough to understand that sometimes, as software developers, we can become enamored with new toys that are entertaining, and possibly educational, but offer little business value. We should choose existing solutions to our problems that are acceptable enough over building our own solutions simply because we want to. For example, a standards-based protocol, like https://github.com/edn-query-language/eql, that allows clients to craft their own queries with little to no server-side updates is preferable to our current bespoke solution. * Be documented and supported. Our choices should have active, helpful, and inclusive development communities built around them. Our choices are: * Rum, https://github.com/tonsky/rum Rum is a solid piece of software, created and maintained by @tonsky, that provides a minimal wrapper around react for creating client-side components, and supports server-side rendering. Although rum does not provide a protocol between client and server, nor a client component state-management solution. * Reagent, https://github.com/reagent-project/reagent Together with Re-frame, https://github.com/Day8/re-frame, this is by far the most popular choice for building reactive client components in Clojurescript. These do not include the server-side solutions we need. * Hoplon, http://hoplon.io Hoplon was created in-house at AdZerk, and later spun-out as an open source project. Hoplon is a complete solution although it uses a less intuitive spreadsheet-like method for building applications with little obvious advantage, and would not be compatible with Datomic without considerable effort. * Luminus, https://luminusweb.com Luminus is a complete solution like Ruby-on-Rails, and is tightly coupled to SQL. Like Hoplon, Luminus would not be compatible with Datomic without considerable effort. * Pedestal, http://pedestal.io Pedestal is supported by Cognitect, the custodians of Clojure and the creators of Datomic. Except Pedestal is best suited for building server-side APIs, and applications that need to stream data in "near real-time" to large numbers of concurrently connected clients. * Fulcro, https://fulcro.fulcrologic.com/ Fulcro is based on Om.Next, provides both front-end and back-end components that work well together, includes tools for building and debugging both, supports server-side rendering, and is supported by a diverse community. Paid commercial support is provided by the core developer team at Fulcro Logic. * Datomic Cloud, https://www.datomic.com Datomic Cloud is a special version of the Datomic database that is tightly integrated with AWS. Datomic Cloud includes a set of Cloud Formation templates for running Datomic in AWS, and taking advantage of AWS specific features, such as auto-scaling groups and load-balancers for distributing traffic across a cluster of Datomic peers. Datomic Cloud also includes Ions, https://docs.datomic.com/cloud/ions/ions.html, to help run Clojure functions as AWS Lambdas. Cognitech claims Datomic Cloud is a suitable framework for building complete applications. Unfortunately Datomic Cloud alone is insufficient. Datomic Cloud lacks a framework for building and testing client-side applications, and a protocol for interacting with Ions.