TimescaleDB vs Prometheus
Twelve of fourteen models named TimescaleDB first on the direct prompt; zero named Prometheus. Both were named by all fourteen models and TimescaleDB carries 70 labels and Prometheus 43, so the shares are not directly comparable.
Named in two categories this edition.
Named in seven 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
TimescaleDBFirst choices, of fourteen modelsPrometheus
Across every category in the October 2026 Edition, TimescaleDB and Prometheus were named in the same answer 100 times, of the 208 answers naming TimescaleDB and the 307 naming Prometheus. In those answers Prometheus took the first choice four times and TimescaleDB fifty-two.
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 | | | | | |
TimescaleDB Prometheus first choice named as an alternative argued againstblank: not namedEach cell is one answer, TimescaleDB on the left and Prometheus on the right.The direct prompt
TimescaleDB first, Prometheus an alternative
12 of 14 modelsPrometheus was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
1 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
1 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
TimescaleDB57%#1 of 9Prometheus2%#6 of 9TimescaleDB63%#1 of 9Prometheus2%#5 of 9TimescaleDB47%#1 of 10Prometheus0%#9 of 10What the models said about TimescaleDB
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of six in this category shown.
“TimescaleDB has lower raw write throughput compared to purpose-built engines like QuestDB for extreme ingest scenarios” Claude Haiku 4.5 · negative prompt · soft negative
“Avoid for massive IoT write-heavy workloads.” DeepSeek V4 Flash · negative prompt · soft negative
“Recommendation for most mid-sized B2B: start with TimescaleDB/Tiger Data if you already use Postgres and need joins between telemetry and CRM/ERP/asset data” Muse Glimmer 30B · paraphrase prompt · first choice
“For most small businesses and startups, TimescaleDB (if you want SQL simplicity) or VictoriaMetrics ... are the strongest budget-friendly choices.” DeepSeek V4 Flash · budget prompt · first choice
“I'd recommend starting with TimescaleDB or InfluxDB Cloud due to their balance of features, ease of use, and managed options.” MiniMax M2.5 · direct prompt · first choice
What the models said about Prometheus
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Two of two in this category shown.
“Prometheus local storage as your only durable, highly available store. ... its local TSDB isn't clustered or replicated.” GPT-6 Luna · negative prompt · soft negative
“Prometheus is by default free to use... Prometheus is an excellent choice as a powerful open-source monitoring and alerting toolkit.” Claude Haiku 4.5 · 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.