About State of DB 2023
Databases power a huge portion of the modern tech industry. And, by extension, the global economy.
You’d think that would make them the subject of countless industry studies, but the conversation around databases is actually relatively quiet.
We’re working hard to change that. Last year we released the first ever State of Databases report, where we surveyed thousands of developers about their favorite database tech.
This year the team at Basedash partnered with our friends at Prisma, Timescale, Airplane, Planetscale, SingleStore and Weaviate. The vast majority of respondents are developers, founders and engineering leaders.
What did we find? To start, it’s clear the world of databases is as diverse as ever, with old products existing alongside brand new ones. For instance, many developers still work with apps powered by OracleDB - a forty-year old product - while thousands of others have flocked to a Postgres setup on Supabase, a company that’s less than five years old.
This year’s edition has fresh data on some familiar questions (SQL vs. NoSQL), along with topics that feel very 2023 (looking at you, vector databases).
We also cover related products like analytics, internal & admin tools, ORMs and hosting providers.
If you’re looking to learn what backend to use for your new project, thinking about how to make your company more productive, or merely curious to learn what developers value in data products, this report is for you.
Read on to learn about the State of Databases in 2023. You can also access the full report, including most of the raw data. Check out the links in the navbar for that.
Methodology and biases
This year we collected data and ranked products based on feedback that respondents gave on each tool. Namely: how they would rate it, whether they had used it, heard of it, and plan to use it again in the future. We also collected demographic data (e.g. years of experience, company size, industry) and opinion data on categories as a whole (e.g. “How happy are you with the state of databases?”). Results were collected through a public online survey shared through social media.
Since some products are obviously more well-known than others, we noticed a popularity bias when compiling the data. Basically, products with a low sample size had a rating that was disproportionately higher or lower relative to other tools in the survey, which skewed their overall rating. We solved this by applying a Bayesian average with C=30 and m=3.7 (the average rating across all tools). This resulted in the final ratings being a balance between the tool’s average rating and the rating of all other tools in the survey, with more of an effect on tools with fewer ratings.
This is the same way IMDb ranks movies, which is why beloved classics like Batman outrank the art house movies your film buff friends are obsessed with.
Our partners for this year shared the survey with their users, and we obviously asked our users to complete the survey as well (10% of respondents were existing Basedash users). Rankings and stats in the survey results were compiled as averages and percentages, meaning that tools with more respondents (including partners) weren’t inherently favored.
We also published the full aggregated response data in a public Basedash workspace which you can access here:
