# TimescaleDB vs InfluxDB: which do AI models recommend for time series dbs, October 2026

IT AI Recommendation Index, October 2026 Edition, Time series databases. Twelve of fourteen models named TimescaleDB first on the direct prompt; three named InfluxDB. Page: https://it-ai-index.com/it-data/time-series-databases/timescaledb-vs-influxdb/

| | First-choice share | Rank | Negative rate | Labels | Models naming it |
|---|---|---|---|---|---|
| TimescaleDB | 63% | #1 of 9 | 3% | 70 | 14 of 14 |
| InfluxDB | 16% | #2 of 9 | 19% | 70 | 14 of 14 |

## The direct prompt, model by model

- Claude Haiku 4.5: both first (first choices: InfluxDB, TimescaleDB) (alternatives: Prometheus)
- MiniMax M2.5: both first (first choices: InfluxDB, TimescaleDB) (alternatives: Amazon Timestream, QuestDB)
- GPT-5.4 mini: timescaledb first (first choices: TimescaleDB) (alternatives: ClickHouse Cloud, InfluxDB, QuestDB)
- Gemini 3.5 Flash: timescaledb first (first choices: TimescaleDB) (alternatives: ClickHouse Cloud, InfluxDB)
- Perplexity Sonar: timescaledb first (first choices: TimescaleDB) (alternatives: Amazon Timestream, InfluxDB, QuestDB)
- Mistral Small: timescaledb first (first choices: TimescaleDB) (alternatives: InfluxDB, QuestDB)
- DeepSeek V4 Flash: timescaledb first (first choices: TimescaleDB) (alternatives: ClickHouse Cloud, InfluxDB, QuestDB)
- Qwen 3.7 Flash: timescaledb first (first choices: TimescaleDB) (alternatives: InfluxDB, QuestDB)
- Kimi K2: timescaledb first (first choices: TimescaleDB) (alternatives: InfluxDB, QuestDB)
- GLM 4.7 FlashX: timescaledb first (first choices: TimescaleDB) (alternatives: ClickHouse Cloud, QuestDB)
- GPT-6 Luna: timescaledb first (first choices: TimescaleDB) (alternatives: ClickHouse Cloud, InfluxDB, Prometheus)
- Muse Glimmer 30B: timescaledb first (first choices: TimescaleDB) (alternatives: InfluxDB, QuestDB)
- Grok 4.1 Fast: influxdb first (first choices: InfluxDB) (alternatives: ClickHouse Cloud, TimescaleDB)
- Llama 4 Maverick: neither named

## What the models said about TimescaleDB

- "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 InfluxDB

- "Older versions (v1) reached end-of-life years ago, with no security patches or support—avoid for new projects." (Grok 4.1 Fast, negative prompt, hard negative)
- "Still risky for production; consider newer versions or alternatives." (GLM 4.7 FlashX, negative prompt, hard negative)
- "For new projects, avoid InfluxDB 1/2." (GLM 4.7 FlashX, negative prompt, hard negative)
- "Start with InfluxDB Cloud if you're new to TSDBs or focused on monitoring/IoT—it's the most adopted, user-friendly for mid-market" (Grok 4.1 Fast, direct prompt, first choice)
- "InfluxDB Cloud or TimescaleDB are often ideal because they balance ease of use, scalability, and cost-effectiveness" (Claude Haiku 4.5, direct prompt, first choice)
- "I'd recommend InfluxDB for most mid-sized B2B companies that need to store and analyze metrics and sensor data." (Mistral Small, paraphrase prompt, first choice)

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. Comparisons are drawn for the top eight products in each category. Published under CC BY 4.0; the output is the models' output, and nothing here is a recommendation by the index.