This document outlines the specific technologies we propose to use in the Fluid Engage services layer. More details about the overall architecture of Engage can be found on the Engage Architecture page.
The Engage services layer aims to weave together the various resources and sources of information required to create a compelling and interactive exhibit experience. We'll talk to content and collections management systems, image stores and asset systems, as well as social networking services on the Web such as YouTube, Wikipedia, and Twitter. Engage will share these resources back out throughout the system ensuring that it's easy to create great user interfaces for both the Web and mobile devices using these services.
For database persistence and searching, we'll use Apache's CouchDB and Lucene products. CouchDB provides us with a Web-friendly, document-oriented database solution that won't force strict schema requirements on our users and implementers.
Goals & Criteria
- Broadly approachable
- Hit the ground running
- Scalable and forward-looking
- Fits the approach of the Fluid community: functional, declarative, Web-oriented
Interoperability is a primary goal of Engage, ensuring that our technologies will work with a wide range of existing authoring tools, content management systems, and other tools databases commonly found in museums and on the Web. The Engage services layer needs to fit in well and leverage open standards wherever possible.
At the same time, our choice for server-side technology needs to be scalable and forward-looking, allowing museums to invest in Engage over the long run, without fear that our services will slow down impossibly when confronted with large collections, and that they won't quickly go obsolete. Engage services also need to be future-proof enough to not quickly become obsolete as the technology landscape evolves.
Lastly, the Fluid community has built up, over the years, a set of techniques and philosophies for writing software: accessibility, the Open Web, functional programming, and markup agnosticism are common themes throughout our technologies. As a community, we embrace diversity and a wide range of styles; shared patterns and techniques in code help make our solutions more coherent and consistent to develop with.
There is an incredible amount of diversity among museums in terms of how they each organize their collections and structure their data. Each museum's collection is different, and it is a daunting and risky task to attempt to force all types of collections into a single schema. Engage will need 's technology needs to embrace this diversity; rather . Rather than creating a "one size fits all" approach at the database level, we'll take a flexible approach to schemas in Engagetreat schemas as flexible.
Given that we can't pre-bake the data model completely, a standard SQL-based relational database in is inappropriate for Engage. A new crop of document-oriented databases has emerged that are well-suited to handling dynamic schemas. Foremost among these is CouchDB, a highly scalable and Web-friendly database written in Erlang.
Data in CouchDB is queried and saved using a RESTful API: fetching data involves fetches use a standard HTTP GET request, while adding or updating documents, just a additions and updates use simple PUT or POST operationoperations. This means that Couch can be used with any programming language, without requiring extra native database drivers. It's also an excellent fit for a Engage's RESTful service-oriented architecture. For museums that already have their own databases or CMS systems, Couch can be replaced with a custom service that provides the same RESTful operations and feeds as provides by the Couch Views that will ship out of the box with Engage.
Users have come to expect natural, Google-like text searches from most modern Web experiences. As a result, Engage will need to include a free text search engine service.
Hands down, the most viable best open source technology for this is Apache's Lucene. Today, it's the fastest and most reliable open source text searching software available, and it has few competitors. Lucene is a JVM-based tool, and should be relatively easy to install in most server environments. Lucene can be easily connected to CouchDB, allowing new documents in Couch to seamlessly be added to the indexes.
Rhino's deployment within the JVM brings with it a number of advantages. We can leverage the Servlet API to provide us with a proven interface to Apache and other Web servers. Since threading in Java is well-establishestablished, and the Servlet API offers clear semantics for concurrency, the JVM offers an easy way to establish a container and framework that is scalable and concurrency-safe.
Portability and JSGI
With a this plan to build first on Rhino and the JVM, and then move to a next-generation runtime as soon as the required Web infrastructure is established for one of thesethey're ready, the obvious problem is portability. If we commit to Rhino now, will be able to move to V8 or Tracemonkey-based environment later?
Env.js for Browser Compatibility
Tying it all Together: Kettle
The Engage services layer will weave together a variety handful of existing technologies to create a new server-side Web development framework called Kettle:
- Rhino + Servlets for the Web container
- JSGI for portability
- Env.js for standard library features and browser compatibiltiy.
- Infusion for application development
The only substantial new code we'll need write is a URL routing scheme, most likely inspired by CherryPy's approach. With this, Kettle will offer a full-featured framework for server-side development.