NoSQL databases · October 2026 Edition
PostgreSQL vs Google Cloud Firestore
Zero of fourteen models named PostgreSQL first on the direct prompt; zero named Google Cloud Firestore. PostgreSQL was named by nine of the fourteen models and Google Cloud Firestore by nine and both carry 11 labels, so the shares below are directly comparable.
Named in six categories this edition.
Named in one category this edition.
First-choice share2%2%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#6#7A position in a field of 13; printed, not drawn.
Labels1111Equal, which is what makes the shares comparable.
The two percentage rows are drawn on one 0 to 100 track, PostgreSQL reading right to left. Rank and label count are printed, not drawn.MongoDB was named alongside these two in fourteen of the fourteen direct answers. MongoDB vs PostgreSQL · MongoDB vs Google Cloud Firestore · Amazon DynamoDB vs PostgreSQL
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 nosql 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.
PostgreSQLFirst choices, of fourteen modelsGoogle Cloud Firestore
Direct00
Paraphrase00
Comparative00
Budget-constrained01
Scale-constrained10
Negative10
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.
Every model, every framing
The eighty-four answers behind the chart above, one cell each: where PostgreSQL and Google Cloud Firestore stood in it.
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| 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 |
PostgreSQL Google Cloud Firestore first choice named as an alternative argued againstblank: not namedEach cell is one answer, PostgreSQL on the left and Google Cloud Firestore on the right.The direct prompt
The plain question, one answer per model, grouped by where PostgreSQL and Google Cloud Firestore stood in it.
Neither was the first choice, one was named
4 of 14 modelsThe answer put something else first and named one of the two as an alternative.Claude Haiku 4.5MongoDB alternatives: Amazon DynamoDB, Google Cloud Firestore, PostgreSQL with JSON
DeepSeek V4 FlashMongoDB alternatives: Amazon DynamoDB, PostgreSQL
Qwen 3.7 FlashMongoDB alternatives: Amazon DynamoDB, Neo4j, PostgreSQL
GPT-6 LunaMongoDB alternatives: Amazon DynamoDB, PostgreSQL
Neither was named
10 of 14 modelsThe answer made no first choice from these two in this category.GPT-5.4 miniMongoDB alternatives: Amazon DynamoDB, Apache Cassandra
Gemini 3.5 FlashMongoDB alternatives: Amazon DynamoDB, Couchbase
Perplexity SonarMongoDB alternatives: Amazon DynamoDB, Azure Cosmos DB
Grok 4.1 FastMongoDB alternatives: Amazon DynamoDB, Apache Cassandra
Mistral SmallAmazon DynamoDB, MongoDB alternatives: Azure Cosmos DB, Redis
Llama 4 MaverickMongoDB
Kimi K2MongoDB alternatives: Couchbase
GLM 4.7 FlashXMongoDB alternatives: Amazon DynamoDB, Apache Cassandra, Couchbase
MiniMax M2.5MongoDB alternatives: Amazon DynamoDB, Couchbase
Muse Glimmer 30BMongoDB alternatives: Amazon DynamoDB
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 Firestore leads by two points.
Google Cloud Firestore6%#3 of 10PostgreSQL5%#4 of 10Mid-marketThe figures above
Level: the same share of first choices.
PostgreSQL2%#6 of 13Google Cloud Firestore2%#7 of 13Enterprise
Level: the same share of first choices.
PostgreSQL0%#– of 9Google Cloud Firestore0%#– of 9What the models said about PostgreSQL
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of three in this category shown.
“Before choosing any NoSQL database, ask yourself: "Why can't I use PostgreSQL?"” Gemini 3.5 Flash · negative prompt · first choice
“If your data is highly normalized and relational ... stick to Postgres.” Qwen 3.7 Flash · scale prompt · first choice
“modern trends suggest looking at PostgreSQL (specifically with JSONB) as the ultimate hybrid solution” Qwen 3.7 Flash · direct prompt · alternative
What the models said about Google Cloud Firestore
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.
“If you do not have IT staff and just want to launch an MVP quickly, start with Firebase (Firestore)” Qwen 3.7 Flash · budget prompt · first choice
“For a managed cloud option, Azure Cosmos DB, Amazon DynamoDB, or Google Cloud Firestore are all common consumption-based choices.” Perplexity Sonar · paraphrase prompt · alternative
“Cloud Firestore has a free quota, including 1 GiB of stored data, 50,000 reads/day” GPT-6 Luna · budget prompt · alternative
Also compared
MongoDB vs PostgreSQLMongoDB vs Google Cloud FirestoreAmazon DynamoDB vs PostgreSQLAmazon DynamoDB vs Google Cloud FirestoreCouchbase vs PostgreSQLCouchbase vs Google Cloud FirestoreRedis vs PostgreSQLRedis vs Google Cloud FirestoreScyllaDB vs PostgreSQLScyllaDB vs Google Cloud FirestoreAll twenty-one head-to-head pages and the full nosql standing
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.