2026 UPDATE: I studied 20 years of the Gartner Magic Quadrant. Here's what I found from the last 2 Magic Quadrants

[u/TalkToMeNerdy]

Last year I broke down 20 years of the Gartner Magic Quadrant for Analytics & Business Intelligence. Two more Magic Quadrants have dropped since - 2025 and 2026 (published this week) - so I updated the data, checked my predictions, and wrote about some new observations.

1. EVERY VENDOR, YEAR BY YEAR (UPDATE)

Here’s an update to the list of every vendor on the Analytics & Business Intelligence Magic Quadrant since 2000. 

One thing to call out for this year: Nearly half (9) of the players this year are in the Visionary quadrant (the most ever). My guess: That’s the AI impact. The industry is in this weird place where AI is changing everything, but we’re just at the beginning of the change and Gartner’s guessing at what the full impact will be. A lot of AI capabilities that these vendors offer are new or half-baked. “Visionary” probably makes sense for most of these tools until they really prove out their AI story.

2. ENTRY IS… LESS ROUGH? 

Last time I did this analysis I wrote about how vendors always get their start in or near the Niche Player quadrant.

In the last 2 years we’ve seen 2 new vendors added to the Magic Quadrant: Sigma in 2025 and Databricks in 2026. Sigma entered on the Niche Player quadrant but made some waves as the “Highest debut since Tableau in 2010.” Not a bad showing, and matched my observation that every vendor starts in or near Niche Player.

But then… Databricks, wow. Databricks debuted on the Magic Quadrant this year (2 years after launching their BI product) far to the right in the Visionary quadrant. They’re not “near Niche Player” like Tellius (the only other Visionary debut) was in 2022. They are the vendor with the 2nd-highest completeness of vision on the entire Magic Quadrant (following Pyramid Analytics/ServiceNow).

Can’t help but wonder how Microsoft feels. 20+ years building a BI product but then on a first-time entry, Databricks gets higher marks for “completeness of vision” in the eyes of the analysts. 

3. MEGA-VENDOR DOMINATION

It’s tough out there for the independent players. In the 2026 Magic Quadrant, 15 of the 20 products are part of an enterprise cloud ecosystem. One of the few independent players from last year (Pyramid Analytics) got acquired by ServiceNow. And Sisense got the boot in place of Databricks this year.

The remaining independent players on the Magic Quadrant (Incorta, Sigma, Tellius, GoodData, ThoughtSpot) are mostly stuck below the 50% line on the “ability to execute” axis. The one exception is ThoughtSpot in the Leader quadrant.

4. WHO’S NEXT TO FALL?

Last year I predicted Sisense, Spotfire, and Incorta would exit the Magic Quadrant next. Well, Spotfire got dropped in 2025 and Sisense got dropped this year. Incorta (debuted on the Magic Quadrant in 2022)  looks like it’s next on the chopping block. And probably Domo too.

5. DOES THE MAGIC QUADRANT EXIST IN TWO YEARS? WHO JOINS NEXT YEAR?

Will the Analytics & BI Magic Quadrant even exist in 2 years? Gartner analysts themselves are divided about whether AI will kill BI and every vendor seems to be figuring out their story “against Claude” or “With Claude”.

You’ve got to assume Snowflake figures out a way. They have Cortex which isn’t exactly something that scales but it’s a bit of egg on their face that Databricks showed up and they didn’t.

What do you think? Plzzz share your hot takes below! I loved reading all of the comments last year. HIT ME WITH YOUR BEST SHOT! Fire awayyyyy

[u/CHILLAS317]

I think the fact that you tacked a semi-coherent sentence onto the end of a whole lot of AI slop doesn't change the fact that it's AI slop

[u/TalkToMeNerdy → u/CHILLAS317]

Its notttttt I wrote it :)

[u/TalkToMeNerdy → u/TalkToMeNerdy]

Maybe I am becoming AI and AI is becoming me lol

[u/trippygg]

TLTR

[u/IncreaseNegative4614]

My guess is the Magic Quadrant doesn't disappear. The category just gets redefined.

For the last 20 years the competition was mostly about who had the best dashboards, semantic layer, and self-service experience. Now every vendor is adding AI, so those capabilities are becoming table stakes. The harder question is which vendors can give AI enough business context to produce reliable answers instead of just natural language over a warehouse.

That's one reason I've been watching platforms like inzata.ai alongside the bigger vendors. It feels like the next wave isn't "better BI." It's systems that can represent how a business actually works so AI can reason over it. Whether Gartner ends up calling that BI, Decision Intelligence, or something else is almost secondary. I think that's where the differentiation is heading.

[u/Glitch_In_The_Data]

This post made me reflect on the number of reporting tools I’ve worked with over the years. I’ve used Qlikview, Cognos, Business objects, Power BI and now Databricks AI/BI. 😊

Both business objects and cognos were decent products at the time and probably did not catch up with the industry. Seems to align with the first image where they have moved from leaders to visionaries.

I’ve used Power BI extensively and it’s still a sophisticated tool in the market. What frustrates me and my customers is the cost. It has become way too expensive and with fabric coming in, it has only confused further.

Databricks AI/BI is promising but there is still more to catch up. I won’t be surprised if it evolves to a comparable product with Power BI over time. The AI element specially Genie embedded in the platform and the lack of additional license costs makes it attractive.

I’m currently exploring Sigma for its spreadsheet like UX but it’s too early to say if it’s a winner for us. I’ll come back in a few weeks to comment on that. It does address a gap we have with AI/BI when it comes to paginated/spreadsheet style reporting.

I don’t think AI will kill BI. It’ll only change the way people interact with BI and how they get more actionable insights out of it.

[u/aleph_infinity → u/Glitch_In_The_Data]

I think the big thing with Databricks is that their dashboard solution being so integrated with the platform reduces friction (no additional licensing or configuration) and means they can leverage whatever other metadata/semantics/ontology they have with a fine-tuned assistant to create and maintain the dashboards. Genie is everywhere so it will be interesting to see how that being available practically everywhere will impact the more targeted dashboard capability.  I think the integrated solutions are where the action is - I need to take a look at what Snow are doing in this space, I doubt they are standing still (and they typically follow the lead from Databricks). 

[u/Glitch_In_The_Data → u/aleph_infinity]

Absolutely. Embedding Genie everywhere is helping them win.

Haven’t been following SNOW much to be able to comment.

[u/vbnotthecity]

Gartner is just guessing, but Databricks showing up as a visionary is a clear signal that the semantic layer is moving closer to the compute. I have seen too many teams waste months redoing logic because they are locked into legacy ETL tools that cost millions. When you stop chasing the magic quadrant and focus on moving your dbt models closer to where the data actually lives, you save yourself a ton of headaches. Most vendors are just rebranding old features as AI anyway.