A Source Code Search Engine makes Programming more Efficient

No matter your experience level as a software engineer, being able to quickly find code examples helps make your job a bit easier. Most developers know how to write a complex Google search query, as well as being able to navigate GitHub. Nonetheless, having a dedicated source code search engine offers the potential to become more efficient at writing software.

A nascent software developer feels the same way, and is working on a search engine dedicated to finding those valuable code snippets that inspire a solution to a pressing problem. This approach also offers the potential to make learning new languages an easier process. Let’s take a closer look at his efforts.

Learning New Programming and discovering New Functionality

After being exposed to software engineering as part of his college education, Canadian developer, Anthony Nguyen felt there had to be a better way to find relevant code examples. Sure, a Google search helps somewhat, but what about a dedicated search engine specifically for source code? Nguyen began work on SyntaxDB, a tool he hopes to someday be an essential part of any developer’s toolbox.

Michael Byrne first reported on Nguyen’s efforts earlier this year at Motherboard on Vice.com. If Nguyen makes SyntaxDB a success, it becomes another key to making the modern software development team work more efficiently. Interested developers are able to use this emerging resource today.

Byrne notes the tool’s utility for seeing how a common code pattern or piece of functionality gets written in an unfamiliar language. Considering the rapid rate of change in the software development world, new languages and functional libraries get introduced regularly. Having SyntaxDB at the ready helps to speed up the learning process for any programmer.

The Developer Community helping SyntaxDB build its Content

One current weakness noted by Byrne involves SyntaxDB’s relative lack of reference documentation. At the time of his article, it appeared Nguyen himself produced a lot of the internal content returned in the search results.

A robust community of developers willing to help add material to the SyntaxDB database has come to the rescue; potentially increasing the amount of content referenced by the search engine. It currently provides references to many popular languages, including Java, C, C++, C#, Ruby, Go, Swift, Python, and JavaScript.

Adding extensions to allow SyntaxDB to work within the most popular IDE’s is another way Nguyen needs support. He built one for Visual Studio Code and other contributor wrote one for Atom. Nguyen hopes to eventually integrate SyntaxDB into every major IDE and source code editor – a worthy goal, indeed.

Nguyen also wants input from other developers on how to refine the search engine’s interface. He also encourages developers to submit any corrections to the tool’s current source code examples. His current major project with SyntaxDB involves building an interface to easily allow content contributions from other software engineers.

With a goal of becoming the fastest programming reference in the world, Anthony Nguyen gives hope to developers struggling to learn a new programming language or simply how to do something new. Take some time to use SyntaxDB and offer feedback and even add some content of your own.

Stay tuned to the Betica Blog for further insights on the growing software development world. As always – thanks for reading!

A Closer Look at the MEAN Stack

The LAMP stack – which stands for Linux, Apache, MySQL, and PHP – has been standard practice for web development at many shops for nearly a decade. Since the one constant in the technology world is its rapid pace of change, it stands to reason a new standard is emerging in this software development space. The MEAN stack leverages many recent innovations in technology, including NoSQL databases in addition to some popular JavaScript libraries.

What follows is a high level overview of the MEAN stack to give you some food for thought before architecting your next web development project. Leverage these insights to make an informed decision on which development stack works best for your needs.

What is “MEAN?”

The MEAN stack is made up of MongoDB, one of the most preeminent NoSQL databases, used in combination with three popular JavaScript frameworks, ExpressJS, AngularJS, and Node.js. The fact that nearly all code for a MEAN project – from database to client – is written in JavaScript is one of the main reasons for its rapid growth. If your organization boasts a lot of JavaScript coding talent, it makes MEAN worthy of consideration on your next web project.

The Four Components of the MEAN Stack

MongoDB is a NoSQL document database widely popular for all kinds of applications. MongoDB is also available through many Cloud service providers, including Amazon AMS, Microsoft Azure, and Google Cloud. It leverages the JSON format for data transfer, making it highly appropriate as the database of choice for MEAN.

A lightweight framework for architecting web applications, ExpressJS was inspired by the popular Ruby library, Sinatra. It is a high performance framework well suited for both scalability and concurrency. It also facilitates the creation of unique APIs specifically for use in a web application.

AngularJS is a Google-developed framework for quickly building web-based user interfaces. It makes the creation of dynamic web pages a breeze; leveraging two-way data binding along with other useful features, including client-side code execution and support for the MVC model. Angular’s extensibility and flexibility enhances its compatibility with other frameworks and libraries, in addition to being a major component of the MEAN stack.

Node.js provides the server side execution environment for a MEAN application. Expect a high scalability factor even with a server farm charged with hosting multiple applications. Built upon version 8 of the Chrome JavaScript runtime engine, Node.js by itself is growing in usage among development teams.

The Advantages of the MEAN Stack

Obviously, the fact that all server and client code is written in JavaScript remains of the major advantages of the MEAN stack. Companies are able to take advantage of their staff’s familiarity with a scripting language that’s been around for two decades. Any overall learning curve is lessened by simply focusing on learning MEAN’s three libraries and MongoDB. 

The scalability features of ExpressJS and Node.js make the MEAN stack suitable for the highly concurrent web applications currently in vogue throughout the technology world. The flexibility of the libraries used in MEAN make it easy to swap out any of the components for a library (or database) more familiar to your development staff. It is definitely worthy of exploration for use in your team’s next web development project.

Keep returning to the Betica Blog for additional dispatches from the wide world of software development. Thanks for reading!

The NoSQL Capabilities of PostgreSQL

Many businesses of all sizes leverage PostgreSQL as an open source option to Oracle and other relational databases. Significant cost savings while maintaining a similar level of performance remains a preeminent reason for this switch. A robust community and the availability of commercial-grade support make Postgres worthy of consideration for your traditional database needs. 

With NoSQL gaining popularity all over the technology world, you may wonder how PostgreSQL supports this new database paradigm. Let’s take a look at what functionality exists today in the database with a quick towards the future as well.

Postgres NoSQL for the Enterprise

We’ve talked about EnterpriseDB’s commercial level version of PostgreSQL previously on the blog. The company also offers a Postgres version with support for document databases and key-value stores – two of the most common NoSQL database types. Known as Postgres NoSQL for the Enterprise, this is something worthy of closer attention at companies looking for an open source mix of relational and NoSQL databases.

This Postgres database solution combines the speed and flexibility of NoSQL with the traditional SQL database functionality required for enterprise use – most notably the support for ACID (atomic, consistent, isolated, and durable) transactions. Database instances also easily integrate into the existing business data infrastructure, no matter the platform. In short, it provides the best of both worlds – relational and NoSQL.

ACID transactions are vital for business organizations that depend on the real-time validity of the relationships within its data. Many current NoSQL databases don’t offer this feature, instead following the BASE paradigm which emphasizes speed and availability over the consistency of the data. Postgres NoSQL lets companies combine unstructured and structured data; mixing the performance of NoSQL with the more formalized governance of traditional SQL.

Postgres NoSQL supports many industry standards for programmatic access and data exchange. These include Ruby, Python, and JavaScript for the former, and the JSON and XML formats in the latter case. The superior performance of PostgreSQL combined with the seamless scalability typical of a NoSQL database solution make EnterpriseDB’s combination of Postgres and NoSQL a valid option for any business desiring a flexible database infrastructure.

The Future of PostgreSQL and NoSQL

In a previous article looking at new features of PostgreSQL 10, we noted the relative lack of NoSQL functionality in this newest version of Postgres, slated for release later this year. The new XMLTABLE feature supports the direct querying of data stored in XML documents. Other performance improvements in version 10 bring the speed of the relational database closer to its other NoSQL brethren.

One recent enhancement in Amazon Web Services deserves mention for companies using a mixture of relational and NoSQL databases. The AWS database migration service now includes NoSQL databases, with MongoDB (as a source) and Amazon’s own DynamoDB (as a target) being the first two to be supported. This means companies with a PostgreSQL instance on AWS are able to stream data from Postgres to a DynamoDB instance.

Companies with an investment in PostgreSQL need to explore EnterpriseDB’s NoSQL option to see if any of its features make sense for adding non-traditional database formats to the corporate data infrastructure.

Keep returning to the Betica Blog for additional news and insights from the wide world of software development. Thanks for reading!