QuestDB vs PostgreSQL
Zero of fourteen models named QuestDB first on the direct prompt; zero named PostgreSQL. QuestDB was named by fourteen of the fourteen models and PostgreSQL by ten and QuestDB carries 57 labels and PostgreSQL 12, so the shares are not directly comparable.
Named in two categories this edition.
Named in six categories this edition.
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 time series databases page.
By framing
QuestDBFirst choices, of fourteen modelsPostgreSQL
Across every category in the October 2026 Edition, QuestDB and PostgreSQL were named in the same answer twenty-six times, of the 153 answers naming QuestDB and the 106 naming PostgreSQL. In those answers PostgreSQL took the first choice two times and QuestDB three.
Every model, every framing
| 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 | | | | |
QuestDB PostgreSQL first choice named as an alternative argued againstblank: not namedEach cell is one answer, QuestDB on the left and PostgreSQL on the right.The direct prompt
Neither was the first choice, one was named
9 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
5 of 14 modelsThe answer made no first choice from these two in this category.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
What the models said about QuestDB
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of six in this category shown.
“QuestDB is strong for time-centric analytics, but it is not the best choice if most of your queries do not filter by time” Perplexity Sonar · negative prompt · soft negative
“QuestDB (SQLi)” GLM 4.7 FlashX · negative prompt · soft negative
“1. QuestDB: A time series database that is designed to handle large amounts of data and provide fast query performance.” Llama 4 Maverick · paraphrase prompt · first choice
“specialized TSDBs like InfluxDB, TimescaleDB, or QuestDB are generally safer choices” Mistral Small · negative prompt · first choice
“For new projects in 2026, I'd strongly lean toward QuestDB” DeepSeek V4 Flash · negative prompt · first choice
What the models said about PostgreSQL
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of four in this category shown.
“they are not optimized for large volumes... making them poor choices for serious time series workloads” Mistral Small · negative prompt · hard negative
“PostgreSQL, MySQL, and SQL Server are fine for *small-scale* time-series workloads, but ... they become a poor fit as ingest volume, retention, and query complexity grow.” Perplexity Sonar · negative prompt · soft negative
“General-purpose databases like PostgreSQL or MySQL can handle time-series workloads at small scale, but performance degrades” Claude Haiku 4.5 · negative prompt · soft negative
“Start with PostgreSQL + TimescaleDB if your scale is modest. It minimizes new tooling and hiring complexity.” GPT-5.4 mini · budget prompt · first choice
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.