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Managed relational databases · October 2026 Edition

Amazon Aurora vs Google Cloud SQL

Four of fourteen models named Amazon Aurora first on the direct prompt; two named Google Cloud SQL. Amazon Aurora was named by thirteen of the fourteen models and Google Cloud SQL by fourteen and Amazon Aurora carries 39 labels and Google Cloud SQL 66, so the shares are not directly comparable.

Amazon Aurora

accepted challenger

Named in two categories this edition.

Google Cloud SQL

accepted challenger

Named in one category this edition.

First-choice share12%10%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate21%12%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#2#3A position in a field of 9; printed, not drawn.
Labels3966A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Amazon Aurora reading right to left. Rank and label count are printed, not drawn.Amazon RDS was named alongside these two in twelve of the fourteen direct answers. Amazon RDS vs Amazon Aurora · Amazon RDS vs Google Cloud SQL · Amazon Aurora vs Neon

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 managed relational databases page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
Amazon AuroraFirst choices, of fourteen modelsGoogle Cloud SQL
Direct42
Paraphrase321 against Amazon Aurora
Comparative51
Budget-constrained011 against Google Cloud SQL
Scale-constrained01
Negative006 against Amazon Aurora · 7 against Google Cloud SQL
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, Amazon Aurora and Google Cloud SQL were named in the same answer seventy-six times, of the 107 answers naming Amazon Aurora and the 186 naming Google Cloud SQL. In those answers Google Cloud SQL took the first choice two times and Amazon Aurora twenty-one.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where Amazon Aurora and Google Cloud SQL 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
Amazon Aurora Google Cloud SQL first choice named as an alternative argued againstblank: not namedEach cell is one answer, Amazon Aurora on the left and Google Cloud SQL on the right.

The direct prompt

The plain question, one answer per model, grouped by where Amazon Aurora and Google Cloud SQL stood in it.

Amazon Aurora first, Google Cloud SQL an alternative

4 of 14 modelsGoogle Cloud SQL was named in the answer but not as the choice, or not at all.
GPT-5.4 miniAmazon Aurora, Amazon RDS alternatives: Azure Database for PostgreSQL, Azure SQL Database, Google Cloud SQL
Gemini 3.5 FlashAmazon Aurora alternatives: Aiven, AlloyDB for PostgreSQL, Azure SQL Database, Neon
Mistral SmallAmazon Aurora alternatives: Azure SQL Database, Google Cloud SQL
Llama 4 MaverickAmazon Aurora, Amazon RDS alternatives: Ntirety, Rackspace Technology

Google Cloud SQL first, Amazon Aurora not the choice

2 of 14 modelsAmazon Aurora was named in the answer but not as the choice, or not at all.
Grok 4.1 FastGoogle Cloud SQL alternatives: Aiven, Amazon RDS, Azure SQL Database, DigitalOcean Managed Databases
GLM 4.7 FlashXGoogle Cloud SQL alternatives: Amazon RDS, Azure Database

Neither was the first choice, one was named

6 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Perplexity SonarAmazon RDS alternatives: Azure SQL Database, Google Cloud SQL
DeepSeek V4 FlashAmazon RDS alternatives: Azure SQL Database, Google Cloud SQL
Kimi K2Amazon RDS alternatives: Amazon Aurora, Azure SQL Database, Google Cloud SQL, Neon
MiniMax M2.5Amazon RDS alternatives: Amazon Aurora, DigitalOcean Managed Databases, Google Cloud SQL
GPT-6 LunaAmazon RDS alternatives: Amazon Aurora, Azure Database for PostgreSQL, Google Cloud SQL
Muse Glimmer 30BAmazon RDS alternatives: Amazon Aurora, Azure SQL Database, Google Cloud SQL

Neither was named

2 of 14 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5Amazon RDS alternatives: Azure SQL Database
Qwen 3.7 FlashAmazon RDS alternatives: Azure Database for SQL Server / PostgreSQL, Neon, Vercel Postgres

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
Google Cloud SQL leads by fifteen points.
Google Cloud SQL16%#3 of 8
Amazon Aurora1%#7 of 8
The full small business standing →
Mid-marketThe figures above
The order flips: Amazon Aurora leads at mid-market.
Amazon Aurora12%#2 of 9
Google Cloud SQL10%#3 of 9
The full mid-market standing →
Enterprise
Amazon Aurora leads by seventeen points.
Amazon Aurora26%#1 of 8
Google Cloud SQL9%#4 of 8
The full enterprise standing →

What the models said about Amazon Aurora

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

“Experts advise caution or avoidance for production environments where stable performance is critical.” Mistral Small · negative prompt · hard negative
“Aurora uses internal optimizations and sometimes proprietary features ... that can make migrating back to standard MySQL/Postgres difficult” Qwen 3.7 Flash · negative prompt · soft negative
“While Aurora is popular, be cautious about: Complex pricing - I/O charges can escalate unpredictably” Kimi K2 · negative prompt · soft negative
“a recommended hosted SQL database could be PostgreSQL with a cloud-managed service like AWS Aurora, as it balances capability, cost, and operational simplicity” Llama 4 Maverick · paraphrase prompt · first choice
“Pick AWS RDS/Aurora for broadest engine breadth and ecosystem maturity, and for cloud-native Aurora performance with MySQL/PostgreSQL compatibility.” Muse Glimmer 30B · comparative prompt · first choice
“is Amazon Relational Database Service (RDS) or Amazon Aurora, as they are fully managed relational database services” Llama 4 Maverick · direct prompt · first choice

What the models said about Google Cloud SQL

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

“extended support is paid, and Cloud SQL automatically enrolls EOL-version instances. Check the exact engine version and upgrade dates before committing.” GPT-6 Luna · negative prompt · soft negative
“it has the same class of cautions as other DBaaS offerings: you should check pricing, scaling model, maintenance control...” Perplexity Sonar · negative prompt · soft negative
“Less ideal for global/multi-region strong consistency writes.<br>- Scaling not as elastic for extreme loads.” Grok 4.1 Fast · negative prompt · soft negative
“I'd recommend considering Amazon RDS (Relational Database Service) or Google Cloud SQL as your primary options” GLM 4.7 FlashX · paraphrase prompt · first choice
“The top managed relational database services are Amazon RDS, Google Cloud SQL, Azure SQL Database” Perplexity Sonar · comparative prompt · first choice
“Amazon RDS or Google Cloud SQL offer the best balance of features, scalability, and reliability” Claude Haiku 4.5 · paraphrase prompt · first choice
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.