What is Node.js and what are its top alternatives?
Node.js alternatives & related posts
related AngularJS posts
When Redash was created 5 years ago we chose AngularJS as our frontend framework, but as AngularJS was replaced by Angular 2 we had to make a new choice. We decided that we won't migrate to Angular, but to either React or Vue.js. Eventually we decided to migrate to React for the following reasons:
- Many in our community are already using React internally and will be able to contribute.
- Using react2angular we can do the migration gradually over time instead of having to invest in a big rewrite while halting feature development.
So far the gradual strategy pays off and in the last 3 major releases we already shipped React code in the Angular.js application.
related PHP posts
When I joined NYT there was already broad dissatisfaction with the LAMP (Linux Apache HTTP Server MySQL PHP) Stack and the front end framework, in particular. So, I wasn't passing judgment on it. I mean, LAMP's fine, you can do good work in LAMP. It's a little dated at this point, but it's not ... I didn't want to rip it out for its own sake, but everyone else was like, "We don't like this, it's really inflexible." And I remember from being outside the company when that was called MIT FIVE when it had launched. And been observing it from the outside, and I was like, you guys took so long to do that and you did it so carefully, and yet you're not happy with your decisions. Why is that? That was more the impetus. If we're going to do this again, how are we going to do it in a way that we're gonna get a better result?
So we're moving quickly away from LAMP, I would say. So, right now, the new front end is React based and using Apollo. And we've been in a long, protracted, gradual rollout of the core experiences.
React is now talking to GraphQL as a primary API. There's a Node.js back end, to the front end, which is mainly for server-side rendering, as well.
Behind there, the main repository for the GraphQL server is a big table repository, that we call Bodega because it's a convenience store. And that reads off of a Kafka pipeline.
For markup and style, I used Pug and Sass, since they’re the perfect match to me. I love the clean and strict syntax of both of them and even more that their structure is almost similar. Also, both of them come with an expanded functionality such as mixins, loops and so on related to their “siblings” (HTML and CSS). Both of them require nesting and prevent untidy code, which can be a huge advantage when working in teams. I used JSON to store data (since the data quantity on my website is moderate) – JSON works also good in combo with Pug, using for loops, based on the JSON Objects for example.
To send my contact form I used PHP, since sending emails using PHP is still relatively convenient, simple and easy done.
DevOps: Of course, I used Git to do my version management (which I even do in smaller projects like my website just have an additional backup of my code). On top of that I used GitHub since it now supports private repository for free accounts (which I am using for my own). I use Babel to use ES6 functionality such as arrow functions and so on, and still don’t losing cross browser compatibility.
Side note: I used npm for package management. 🎉
related Python posts
Winds 2.0 is an open source Podcast/RSS reader developed by Stream with a core goal to enable a wide range of developers to contribute.
Recently we were looking at a few robust and cost-effective ways of replicating the data that resides in our production MongoDB to a PostgreSQL database for data warehousing and business intelligence.
We set ourselves the following criteria for the optimal tool that would do this job: - The data replication must be near real-time, yet it should NOT impact the production database - The data replication must be horizontally scalable (based on the load), asynchronous & crash-resilient
Based on the above criteria, we selected the following tools to perform the end to end data replication:
We chose MongoDB Stitch for picking up the changes in the source database. It is the serverless platform from MongoDB. One of the services offered by MongoDB Stitch is Stitch Triggers. Using stitch triggers, you can execute a serverless function (in Node.js) in real time in response to changes in the database. When there are a lot of database changes, Stitch automatically "feeds forward" these changes through an asynchronous queue.
We chose Amazon SQS as the pipe / message backbone for communicating the changes from MongoDB to our own replication service. Interestingly enough, MongoDB stitch offers integration with AWS services.
In the Node.js function, we wrote minimal functionality to communicate the database changes (insert / update / delete / replace) to Amazon SQS.
Next we wrote a minimal micro-service in Python to listen to the message events on SQS, pickup the data payload & mirror the DB changes on to the target Data warehouse. We implemented source data to target data translation by modelling target table structures through SQLAlchemy . We deployed this micro-service as AWS Lambda with Zappa. With Zappa, deploying your services as event-driven & horizontally scalable Lambda service is dumb-easy.
In the end, we got to implement a highly scalable near realtime Change Data Replication service that "works" and deployed to production in a matter of few days!