AI Indexes
IT AI Index
Index › Cloud and infrastructure › Colocation › DataBank vs CoreSite
Colocation providers · October 2026 Edition

DataBank vs CoreSite

Three of fourteen models named DataBank first on the direct prompt; one named CoreSite. DataBank was named by nine of the fourteen models and CoreSite by thirteen and DataBank carries 15 labels and CoreSite 33, so the shares are not directly comparable.

DataBank

accepted challenger

Named in one category this edition.

CoreSite

accepted challenger

Named in one category this edition.

First-choice share10%5%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%0%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#4#5A position in a field of 9; printed, not drawn.
Labels1533A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, DataBank reading right to left. Rank and label count are printed, not drawn.TierPoint was named alongside these two in eight of the fourteen direct answers. TierPoint vs DataBank · TierPoint vs CoreSite · Flexential vs DataBank

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the colocation providers page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
DataBankFirst choices, of fourteen modelsCoreSite
Direct31
Paraphrase11
Comparative00
Budget-constrained00
Scale-constrained00
Negative00
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.

Across every category in the October 2026 Edition, DataBank and CoreSite were named in the same answer twenty-five times, of the 37 answers naming DataBank and the 94 naming CoreSite. In those answers CoreSite took the first choice one time and DataBank three.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where DataBank and CoreSite stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
Claude Haiku 4.5
GPT-5.4 mini
Gemini 3.5 Flash
Perplexity Sonar
Grok 4.1 Fast
Mistral Small
DeepSeek V4 Flash
Llama 4 Maverick
Qwen 3.7 Flash
Kimi K2
GLM 4.7 FlashX
MiniMax M2.5
GPT-6 Luna
Muse Glimmer 30B
DataBank CoreSite first choice named as an alternative argued againstblank: not namedEach cell is one answer, DataBank on the left and CoreSite on the right.

The direct prompt

The plain question, one answer per model, grouped by where DataBank and CoreSite stood in it.

DataBank first, CoreSite not the choice

3 of 14 modelsCoreSite was named in the answer but not as the choice, or not at all.
Grok 4.1 FastDataBank, TierPoint alternatives: Equinix
Mistral SmallDataBank, Equinix
Qwen 3.7 FlashDataBank, Digital Realty alternatives: Equinix, NTT Global Data Centers

CoreSite first, DataBank not the choice

1 of 14 modelsDataBank was named in the answer but not as the choice, or not at all.
Perplexity SonarCoreSite alternatives: Iron Mountain Data Centers, NTT Global Data Centers

Neither was the first choice, one was named

7 of 14 modelsThe answer put something else first and named one of the two as an alternative.
GPT-5.4 miniEquinix alternatives: CoreSite, Flexential, TierPoint
Gemini 3.5 FlashFlexential alternatives: Centersquare, CoreSite, Iron Mountain Data Centers, TierPoint
DeepSeek V4 FlashFlexential alternatives: DataBank, TierPoint
Kimi K2TierPoint alternatives: Cologix, DataBank
GLM 4.7 FlashXFlexential, TierPoint alternatives: CoreSite, CyrusOne, DataBank, Iron Mountain Data Centers, QTS
GPT-6 LunaFlexential alternatives: CoreSite, Equinix, TierPoint
Muse Glimmer 30BTierPoint alternatives: CoreSite, CyrusOne, Cyxtera, DataBank, Equinix, Flexential, NTT

Neither was named

3 of 14 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5no first choice
Llama 4 Maverickno first choice
MiniMax M2.5no first choice

Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.

By buyer segment

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
DataBank leads by six points.
DataBank6%#3 of 8
CoreSite0%#7 of 8
The full small business standing →
Mid-marketThe figures above
DataBank leads by five points.
DataBank10%#4 of 9
CoreSite5%#5 of 9
The full mid-market standing →
Enterprise
The order flips: CoreSite leads at enterprise.
CoreSite11%#3 of 9
DataBank0%#– of 9
The full enterprise standing →

What the models said about DataBank

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.

“Start with DataBank or Digital Realty for a balance of price, performance, and reliability.” Qwen 3.7 Flash · direct prompt · first choice
“I'd start with DataBank, in the metro closest to your users and IT staff.” GPT-6 Luna · paraphrase prompt · first choice
“DataBank and TierPoint shine for mid-market value/compliance” Grok 4.1 Fast · direct prompt · first choice

What the models said about CoreSite

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.

“CoreSite: Best Overall for High Support & Cloud Connectivity (US-focused)” Gemini 3.5 Flash · paraphrase prompt · first choice
“the best colocation provider is usually CoreSite” Perplexity Sonar · direct prompt · first choice
“CoreSite is often a strong option when you want carrier-neutral colocation with excellent connectivity in key markets.” GPT-5.4 mini · comparative prompt · alternative
Also compared

Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.