Why enterprise software evolves so slowly, despite technological innovation

As the popularity of databases and programming languages ​​shows, companies don’t change their computing paradigms often, if at all.

Image: iStockphoto/metamorworks

The April 2022 DB-Engines Database Popularity Rankings are out, and the big news is…there really isn’t a whole lot of big news. The top 10 databases today are largely the same as last year, or even five years ago. Not that things never change in the database business. In fact, Matthias Gelbmann, co-founder of Solid IT, the company behind DB-Engines’ multi-faceted ranking system, has made a video (best at 2x speed) that shows how rankings have changed over the over time.

Yet it’s still true that change in databases happens slowly, like what we see in programming languages, as Steve O’Grady of Redmonk regularly reminds us. Why? Because both involve large business investments, which rarely change, if at all.

Databases over time

While Gelbmann’s video is worth watching, it’s perhaps even easier to describe the relative stasis in the database rankings through a few screenshots. Here’s how the top 10 databases fare in April 2022:

Stasis table from the 2022 database.
Image: DB Motors

Now let’s go back a year to April 2021, using the Wayback Machine:

Stasis table from the 2021 database.
Image: DB Motors

Like before, right? Well, what about April 2017, five years ago?

Stasis table from the 2017 database.
Image: DB Motors

Ok, now we see some changes, but still not much. Apache Cassandra has fallen out of the top 10 since April 2017, but it hasn’t fallen far: as of April 2022, it’s ranked #11. Not much change. And Elasticsearch, now in the top 10, was right next to it (at #11) in 2017.

What if we go back 10 years to October 2012 (the first time DB-Engines started publishing its ranking)?

Stasis table from the 2012 database.
Image: DB Motors

Memcached (now #30 in 2022) is in the top 10, but otherwise there are very few absolute changes in the popularity of the database, although of course there are significant changes in relative popularity. In other words, Oracle is still at the top of the list, but its relative position is less secure.

Of course, if you want to see significant movement in the rankings, positions 11-25 are in constant motion, but even there, maybe not as much as you think. It’s really in the long tail of databases (50 – 300+) where there’s a seething cauldron of database popularity changes. Google BigQuery, for example, was launched in 2011 but didn’t even reach DB engine ranking thresholds until late 2014. In April 2015, BigQuery failed to make the top 50, but now sits in 24th place. Given how slow the data moves, this kind of ranking improvement suggests dramatic adoption over seven years, measured in terms of jobs, search interest and more.

This should not surprise us. Companies are reluctant to modify their databases, given the sensitivity of the data. Even Amazon, which had deep incentives to leave Oracle, took years to finally accomplish this feat. Databases aren’t the only ones getting the sticky finger treatment, either.

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Future of the programming language

I’m a fan of how Redmonk ranks programming languages, using GitHub and Stack Overflow data. The Redmonk team has been analyzing the evolution of programming language adoption for over a decade. Sometimes O’Grady and his team discover exciting trends. Not recently, however. As O’Grady recently wrote:

The racing story of this quarter – as it has been for a few races now – is stability. Apart from a few notable exceptions which we will discuss in a moment, the rule of language movement in recent years has been that there is little movement. Seventeen of the twenty languages ​​here, in fact, have been stable for three consecutive quarters.

He went on to suggest that “we may be entering an era of relative stasis” with respect to programming languages, “a state where languages ​​have found their respective niches and level with their particular competition.” This “state” has stabilized on a few general-purpose languages ​​(JavaScript ranked first, followed by Python, Java, PHP, with CSS and C# tied for fifth) that developers depend on to do most of their coding. .

SEE: Cheat sheet: How to become a database administrator (free PDF) (TechRepublic)

The reason for this apparent stasis is different but also similar to the stability of database choices: there is significant friction in moving on to something new. In languages, it takes a vendor with huge market power (like Apple) to convince developers to switch to something like Swift or Objective-C. Or it takes a dramatic improvement in security or other concerns, like with Rust, to motivate change.

But most of the time, for most companies, “boring” is a feature, not a bug. That’s why, for databases, programming languages, ERP systems and more, rapid technology innovation doesn’t necessarily mean rapid business adoption. After all, corporations have businesses, not science fairs, to run.

Disclosure: I work for MongoDB, but the opinions expressed here are my own