Time series databases for enterprise buyers
Asked as “time series database”, and as “database for metrics and sensor data”, on behalf of an enterprise B2B company. 58 first choices recorded across the direct, paraphrase, budget and scale prompts, fourteen models each. Added to the November 2026 Edition.
Standing · first-choice share
57%
Clear leader
57TimescaleDB14InfluxDB10VictoriaMetrics19others
57% of first choices, clear leader.
Since October 2026▲+10Since October 2026: 47% → 57%, +10 points. Inside the 11-point floor: within noise.TimescaleDB held the lead, +10 points on 47%, inside the 11-point floor.
By buyer segment
The same question asked on behalf of a different buyer. Each standing is computed within its segment; they sit side by side and are never added together.
Small business
TimescaleDB62%Clear leader▲+5Since October 2026: 57% → 62%, +5 points. Inside the 11-point floor: within noise.Standing →Mid-marketTimescaleDB64%Clear leader▲+1Since October 2026: 63% → 64%, +1 point. Inside the 11-point floor: within noise.Standing →EnterpriseTimescaleDB57%Clear leader▲+10Since October 2026: 47% → 57%, +10 points. Inside the 11-point floor: within noise.This page
TimescaleDB62%Clear leader▲+5Since October 2026: 57% → 62%, +5 points. Inside the 11-point floor: within noise.Standing →Mid-marketTimescaleDB64%Clear leader▲+1Since October 2026: 63% → 64%, +1 point. Inside the 11-point floor: within noise.Standing →EnterpriseTimescaleDB57%Clear leader▲+10Since October 2026: 47% → 57%, +10 points. Inside the 11-point floor: within noise.This pageThe standing
Share is the count of first choices across the direct, paraphrase, budget and scale prompts, over all fourteen models, for an enterprise B2B company. Ordered by share.
ProductFirst-choice shareNegative rateLabelsQuadrantSince October 2026
01TimescaleDB57%4%75endorsed leader▲+10Since October 2026: 47% → 57%, +10 points. Inside the 11-point floor: within noise.47% → 57%
TimescaleDB57%4%75endorsed leader▲+10Since October 2026: 47% → 57%, +10 points. Inside the 11-point floor: within noise.47% → 57%02
InfluxDB14%32%69criticized challenger▼−3Since October 2026: 17% → 14%, −3 points. Inside the 11-point floor: within noise.17% → 14%
InfluxDB14%32%69criticized challenger▼−3Since October 2026: 17% → 14%, −3 points. Inside the 11-point floor: within noise.17% → 14%03
VictoriaMetrics10%10%52accepted challenger▼−5Since October 2026: 15% → 10%, −5 points. Inside the 11-point floor: within noise.15% → 10%
VictoriaMetrics10%10%52accepted challenger▼−5Since October 2026: 15% → 10%, −5 points. Inside the 11-point floor: within noise.15% → 10%04
QuestDB5%15%39accepted challenger▼−3Since October 2026: 8% → 5%, −3 points. Inside the 11-point floor: within noise.8% → 5%
QuestDB5%15%39accepted challenger▼−3Since October 2026: 8% → 5%, −3 points. Inside the 11-point floor: within noise.8% → 5%05
ClickHouse Cloud3%9%43accepted challenger▲+3Since October 2026: 0% → 3%, +3 points. Inside the 11-point floor: within noise.0% → 3%
ClickHouse Cloud3%9%43accepted challenger▲+3Since October 2026: 0% → 3%, +3 points. Inside the 11-point floor: within noise.0% → 3%06Amazon Timestream2%28%40criticized challenger▼−1Since October 2026: 3% → 2%, −1 point. Inside the 11-point floor: within noise.3% → 2%
Show the six products at 0%, ordered by negative rate
12OpenTSDB0%88%16criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%
11
Prometheus0%51%39criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%
Prometheus0%51%39criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%10kdb+0%46%13criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%
09
TDengine0%27%11criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%
TDengine0%27%11criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%08Azure Data Explorer0%12%17accepted challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%
07
Apache Druid0%0%12accepted challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%
Apache Druid0%0%12accepted challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%The floor is 11 points of share, measured: how far the models move a leader on their own when the same questions are asked twice with nothing changed. A larger change is movement; a smaller one can't be told apart from repeat variation, and both are shown. Each index measures its own floor from its own repeat, over its own categories, so the floor differs from one index to the next. Both editions asked the same fourteen models. How the floor is measured
Bars are the share of first choices, 0 to 100Every product with at least 10 labels here. Every product name links to its product page.
For buyers
Head to headHead-to-head pages are published for mid-market buyers, so these open on mid-market figures, not enterprise.
All ten head-to-head pages: the top five products, each against each
One product takes 57% of first choices here, so the chart would put eleven markers in one corner and one at the far edge. The two measurements it plots are columns in the standing above: share, and the negative label rate. Six products carry a negative rate above 25% in this category.
What they warned about
Six of fourteen models held their first choice under the paraphrase. Claude Haiku 4.5, GPT-5.4 mini, Gemini 3.5 Flash, Grok 4.20, Llama 4 Maverick, Qwen 3.7 Flash, Kimi K2 and GPT-6 Luna changed. A high negative share on a product with few labels is a warning. A low share on a product with many labels is salience, not sentiment.
Prometheus51%
20 of 39 labels negative · 14 of 14 models · 7 hard negative
“TSDBs to Avoid or Approach with Caution ... Prometheus (and basic setups) - Why cautious/avoid: Excellent for short-term monitoring but not designed for long-term storage or massive scale.” Grok 4.20, negative prompt
OpenTSDB
88%
14 of 16 labels negative · 13 of 14 models · 9 hard negative
“It is repeatedly flagged with negative labels in enterprise buyer guidance for that operational complexity.” Muse Glimmer 30B, negative prompt
InfluxDB32%
22 of 69 labels negative · 12 of 14 models · 7 hard negative
“avoiding databases like InfluxDB with $25/user/month pricing — which becomes unpredictable and expensive at thousands of users” DeepSeek V4 Flash, budget prompt
Amazon Timestream
28%
11 of 40 labels negative · 8 of 14 models · 4 hard negative
“What to AVOID for Cost Predictability 1. Serverless / Per-Query Billed Databases (e.g., AWS Timestream):” Gemini 3.5 Flash, budget prompt
What they cite
Fourteen of the fourteen models returned a source list in this edition: five return the pages they cited and nine the search results they consulted.
Sites the answers cite
71 of 84 answers in this category came back with a source list, from 13 of 14 models: citations where the model returns them, or the search results it consulted. 906 links across 185 sites, every framing counted. Ranked by the number of answers carrying the site or page. The other 1 model searched through a gateway that returned no source list on this edition. 53 of the 252 answers across every segment cited this index's own page for the category; the method page measures whether that reading tilts an answer.
vendor site · TigerData47 answers · 97 citations · 12 models
vendor site · InfluxData40 answers · 94 citations · 10 models
vendor site · GitHub36 answers · 76 citations · 11 models
vendor site · QuestDB33 answers · 42 citations · 13 models
publisher (Gane)26 answers · 31 citations · 8 models
vendor site · Amazon21 answers · 30 citations · 10 models
21 answers · 24 citations · 10 models
vendor site · G220 answers · 22 citations · 9 models
17 answers · 29 citations · 8 models
vendor site · InfluxData17 answers · 28 citations · 8 models
vendor site · TDengine14 answers · 16 citations · 8 models
12 answers · 12 citations · 8 models
Pages the answers cite
The ten pages named in the most answers, by full address. A page here is one the models returned with a recommendation, not one the index endorses.
24 answers · 8 models
20 answers · 10 models
19 answers · 8 models
18 answers · 8 models
17 answers · 10 models
16 answers · 9 models
16 answers · 9 models
15 answers · 8 models
12 answers · 9 models
12 answers · 8 models
Search against answers
Each company's standing in the answers beside its site's footprint in Google search, one row a site: the products the models named on it with their shares, and the share they add up to; monthly searches on Google, and DataForSEO's estimate of AI search demand (modeled from search signals, directional, not a count of queries to any assistant), for the most-searched of the company's and its products' names (the name is in each row's hover text); estimated monthly organic visits to the site; and its best position in Google's top ten for “best time series database”, “time series database”, “time series databases”. US estimates from DataForSEO and Google's Ads Transparency Center. A small company's site, or a mid-sized company's site for its flagship, is marked company; a product on a large parent's site (Google, Microsoft) has no site figures. A column with no figures for this category is left out, and an empty cell means none were seen, not none exist. Two measurements side by side: neither is read as the cause of the other.
| Company and products | Share | Own site cited | Name searches, Google | AI search demand, est. | Organic visits | Paid search a month, est. | Google ads, last 30 days | Best Google position |
|---|---|---|---|---|---|---|---|---|
| TimescaleDB tigerdata.com TimescaleDB 57%, Tiger Cloud 2% | 59% | 175 | 3,600 | 147 | 23,549 | $658 | 27 | 2 |
| InfluxDB influxdata.com | 14% | 177 | 4,400 | 350 | 46,684 | 44 | 3 | |
| VictoriaMetrics victoriametrics.com | 10% | 132 | 1,300 | 52 | 4,097 | 0 | 6 | |
| QuestDB questdb.com | 5% | 106 | 880 | 6 | 14,289 | 2 | 4 | |
| InfluxDB 3 Enterprise | 5% | 30 | 0 | |||||
| ClickHouse Cloud clickhouse.com | 3% | 168 | 1,000 | 15 | 43,805 | 47 | ||
| Amazon parent site Amazon Timestream 2%, Amazon Timestream for InfluxDB 0% | 2% | 54 | 151,000,000 | 1,380,939 | ||||
| Grafana Cloud grafana.com Grafana Mimir 2%, Grafana 0% | 2% | 277 | 40,500 | 2,627 | 84,520 company | 116 | ||
| Apache Druid druid.apache.org | 0% | 26 | 880 | 27 | 796 | |||
| Azure azure.com Azure Data Explorer 0%, Azure Time Series Insights 0% | 0% | 26 | 301,000 | 47,904 |
Google's top ten for the three searches hold 24 sites; 6 of them are among the sites the models cited here (aws.amazon.com, db-engines.com, influxdata.com, questdb.com, tdengine.com, tigerdata.com). The first result for “best time series database” is reddit.com.
How they answered
Six framings of the same buying question, each sent to every model in a fresh session with search on. One row per model, so a row shows whether it held its answer under rewording, what it named when cost was the constraint, and what it argued against. Computed from the raw judge labels.ShowHide
How they answered
Six framings of the same buying question, each sent to every model in a fresh session with search on. One row per model, so a row shows whether it held its answer under rewording, what it named when cost was the constraint, and what it argued against. Computed from the raw judge labels.
ShowHideModelDirect“What is the best time series database for an enterprise B2B company?”Paraphrase“Which database for metrics and sensor data would you recommend to a large B2B company with thousands of employees?”Comparative“What are the top enterprise-grade time series databases and how do they differ?”Budget-constrained“What is the best time series database for a large company that needs predictable total cost across thousands of users?”Scale-constrained“We are a 5,000 person company with SSO, SOC 2 and procurement review requirements evaluating a time series database. What should we look at?”Negative“Which time series databases should a large enterprise avoid or be cautious about?”
Claude Haiku 4.5InfluxDB, TimescaleDBInfluxDBChangedTimescaleDBagainst: InfluxDBQuestDB, Tiger Cloud, TimescaleDBagainst: InfluxDB Cloud Serverlessno first choiceagainst: Graphite, InfluxDB, OpenTSDB, PostgreSQL, Prometheus, RRDtool
Four alternatives
Apache Cassandra, Prometheus, QuestDB, ScyllaDBTwo alternatives
Prometheus, TimescaleDBOne alternative
QuestDBOne alternative
Amazon TimestreamGPT-5.4 miniInfluxDB 3 Enterprise, TimescaleDBClickHouse CloudChangedInfluxDB 3 EnterpriseGrafana Mimiragainst: Amazon Timestream for LiveAnalyticsInfluxDBagainst: DolphinDB, InfluxDB, Prometheus, TDengine, TimescaleDB, VictoriaMetrics, kdb+
Three alternatives
Amazon Timestream for InfluxDB, ClickHouse Cloud, QuestDBTwo alternatives
InfluxDB, TimescaleDBFive alternatives
Amazon Timestream for InfluxDB, Apache Druid, Azure Data Explorer, ClickHouse Cloud, TimescaleDBTwo alternatives
Tiger Cloud, TimescaleDBTwo alternatives
Mimir, TimescaleDBGemini 3.5 FlashTimescaleDBClickHouse CloudChangedagainst: Amazon TimestreamTimescaleDBVictoriaMetricsagainst: Amazon Timestream, Google BigQueryno first choiceagainst: Amazon Timestream, Azure Data Exploreragainst: Elasticsearch / OpenSearch, Graphite, InfluxDB 1.x / 2.x Open Source, KairosDB, Microsoft SQL Server, MongoDB, MySQL, OpenTSDB, PostgreSQL, Prometheus
Five alternatives
Amazon Timestream, Azure Data Explorer, ClickHouse Cloud, InfluxDB, VictoriaMetricsFour alternatives
Azure Data Explorer, InfluxDB, TimescaleDB, VictoriaMetricsFour alternatives
ClickHouse Cloud, InfluxDB, VictoriaMetrics, kdb+Three alternatives
ClickHouse Cloud, Grafana Mimir, TimescaleDBPerplexity SonarTimescaleDBTimescaleDBHeldno first choiceagainst: DolphinDB, kdb+TimescaleDBagainst: Amazon Timestream, InfluxDBno first choiceagainst: Apache Cassandra, Apache IoTDB, Graphite, InfluxDB, KairosDB, Microsoft SQL Server, MySQL, OpenTSDB, PostgreSQL, Prometheus, QuestDB, TDengine
Eight alternatives
Amazon Timestream, ClickHouse Cloud, InfluxDB, Prometheus, QuestDB, TDengine, Tiger Cloud, VictoriaMetricsThree alternatives
InfluxDB, Prometheus, VictoriaMetricsEight alternatives
Amazon Timestream, ClickHouse Cloud, InfluxDB, Prometheus, QuestDB, TDengine, TimescaleDB, VictoriaMetricsTwo alternatives
ClickHouse Cloud, VictoriaMetricsGrok 4.20InfluxDBagainst: kdb+TimescaleDBChangedagainst: MongoDB, PostgreSQLInfluxDB, TimescaleDBagainst: ClickHouse Cloud, RocksetTimescaleDBagainst: ClickHouse Cloud, InfluxDB, QuestDBInfluxDB, TimescaleDBagainst: Prometheusagainst: Apache Cassandra, Elasticsearch, Graphite, InfluxDB, MongoDB, MySQL, OpenTSDB, PostgreSQL, Prometheus, Redis
Two alternatives
ClickHouse Cloud, TimescaleDBFour alternatives
Amazon Timestream, Apache Cassandra, InfluxDB, ScyllaDBSix alternatives
Amazon Timestream, Apache Druid, Azure Data Explorer, KX, Mimir, PrometheusOne alternative
VictoriaMetricsFive alternatives
Amazon Timestream, Azure Data Explorer, KX, QuestDB, TinybirdMistral SmallTimescaleDBTimescaleDBHeldTimescaleDBTimescaleDBagainst: Amazon Timestream, InfluxDBInfluxDB, TimescaleDB, VictoriaMetricsagainst: Prometheus, Thanosagainst: InfluxDB, KairosDB, Mimir, OpenTSDB, Prometheus
Two alternatives
InfluxDB, VictoriaMetricsFour alternatives
Amazon Timestream, ClickHouse Cloud, Google Cloud Bigtable, InfluxDBSeven alternatives
Amazon Timestream, Azure Data Explorer, Grafana Mimir, InfluxDB, KX, QuestDB, VictoriaMetricsOne alternative
VictoriaMetricsDeepSeek V4 FlashTimescaleDBagainst: InfluxDBTimescaleDBHeldagainst: Prometheus, QuestDBno first choiceTimescaleDBagainst: Amazon Timestream, InfluxDB, VictoriaMetricsQuestDBagainst: TDengineagainst: Amazon Timestream, Azure Data Explorer, InfluxDB, KairosDB, OpenTSDB, Prometheus, kdb+
Two alternatives
Amazon Timestream, VictoriaMetricsTwo alternatives
ClickHouse Cloud, InfluxDBEight alternatives
Amazon Timestream, Azure Data Explorer, ClickHouse Cloud, InfluxDB, Prometheus, TimescaleDB, VictoriaMetrics, kdb+Two alternatives
GreptimeDB, TDengineTwo alternatives
InfluxDB 3 Enterprise, TimescaleDBLlama 4 MaverickTimescaleDBno first choiceChangedno first choiceTimescaleDBQuestDBagainst: InfluxDB, OpenTSDB, PostgreSQL, Prometheus
Two alternatives
InfluxDB, VictoriaMetricsTwo alternatives
InfluxDB, VictoriaMetricsTwo alternatives
Hex, TimescaleDBQwen 3.7 FlashTimescaleDBInfluxDB, TimescaleDBChangedno first choiceagainst: ClickHouse CloudVictoriaMetricsagainst: Amazon Timestream, InfluxDB, Prometheusno first choiceagainst: Graphite, InfluxDB, KairosDB, OpenTSDB, Prometheus, Redis, kdb+
Three alternatives
InfluxDB, QuestDB, VictoriaMetricsThree alternatives
Amazon Timestream, Azure Time Series Insights, ClickHouse CloudFive alternatives
Amazon Timestream, InfluxDB, Prometheus, TimescaleDB, VictoriaMetricsTwo alternatives
QuestDB, TimescaleDBKimi K2InfluxDB, TimescaleDBVictoriaMetricsChangedno first choiceInfluxDB 3 Enterpriseagainst: AVEVA, AWS Timestream LiveAnalytics, InfluxDB, OSI PI, OpenTSDB, PrometheusTimescaleDBagainst: Amazon Timestream, InfluxDB, OSIsoft PI, OpenTSDB, Prometheus, VictoriaMetrics, Wonderware
Two alternatives
ClickHouse Cloud, QuestDBThree alternatives
ClickHouse Cloud, InfluxDB, TimescaleDBEight alternatives
Apache Druid, ClickHouse Cloud, InfluxDB, KX, Prometheus, QuestDB, TimescaleDB, VictoriaMetricsOne alternative
QuestDBFour alternatives
ClickHouse Cloud, InfluxDB, QuestDB, VictoriaMetricsGLM 4.7 FlashXTimescaleDBagainst: QuestDBTimescaleDBHeldno first choiceagainst: PrometheusTimescaleDBagainst: InfluxDBno first choiceagainst: Apache Cassandra, Apache HBase, Apache IoTDB, Couchbase, Elasticsearch, Graphite, InfluxDB v1.x, KairosDB, Microsoft SQL Server, MongoDB, MySQL, OpenTSDB, Oracle, PostgreSQL, Prometheus, QuestDB, Riak, TimescaleDB, kdb+
Five alternatives
ClickHouse Cloud, InfluxDB 3 Enterprise, Prometheus, Thanos, VictoriaMetricsThree alternatives
Amazon Timestream, Azure Time Series Insights, InfluxDBNine alternatives
Aerospike, Amazon Timestream, Apache Druid, ClickHouse Cloud, InfluxDB, KX kdb+ / KDB‑X, QuestDB, TimescaleDB, VictoriaMetricsTwo alternatives
Amazon Timestream, VictoriaMetricsMiniMax M2.5TimescaleDBagainst: ClickHouse Cloud, VictoriaMetricsTimescaleDBHeldInfluxDBAmazon Timestream, VictoriaMetricsagainst: InfluxDBTimescaleDBagainst: QuestDB, VictoriaMetricsagainst: Amazon Timestream, InfluxDB, OpenTSDB, Prometheus, TimescaleDB
Two alternatives
Amazon Timestream, InfluxDBThree alternatives
ClickHouse Cloud, InfluxDB, VictoriaMetricsSix alternatives
Apache Druid, ClickHouse Cloud, Prometheus, QuestDB, TimescaleDB, kdb+Two alternatives
GreptimeDB, QuestDBTwo alternatives
Amazon Timestream, InfluxDB 3 EnterpriseGPT-6 LunaTimescaleDBInfluxDB 3 EnterpriseChangedno first choiceVictoriaMetricsagainst: Amazon Timestream, InfluxDB Cloud Serverlessno first choiceagainst: Amazon Timestream for InfluxDBagainst: Graphite, InfluxDB 1.x or 2.x, OpenTSDB, Prometheus
Two alternatives
ClickHouse Cloud, InfluxDBTwo alternatives
ClickHouse Cloud, PrometheusNine alternatives
Amazon Timestream for LiveAnalytics, Azure Data Explorer, ClickHouse Cloud, Grafana Mimir, InfluxDB 3 Enterprise, QuestDB, Tiger Cloud, TimescaleDB, VictoriaMetricsOne alternative
TimescaleDBFour alternatives
ClickHouse Cloud, InfluxDB, Tiger Cloud, TimescaleDBMuse Glimmer 30BTimescaleDBTimescaleDBHeldTimescaleDBTimescaleDBagainst: InfluxDBno first choiceagainst: Amazon Timestream for LiveAnalytics, InfluxDB, InfluxDB OSS, MySQL, OpenTSDB, PostgreSQL, Prometheus
Six alternatives
Amazon Timestream, Azure Data Explorer, InfluxDB, KX, QuestDB, VictoriaMetricsOne alternative
InfluxDBFour alternatives
ClickHouse Cloud, InfluxDB, QuestDB, VictoriaMetricsOne alternative
Tiger CloudBold is the first choiceAlternatives are counted; the count opens them.What the answer argued against
The record
One row per call: the version string exactly as returned, whether the model searched, sources cited, and latency.
Eighty-four rows: every prompt, every model, every answer.
| Prompt | Model | Version string | Time (UTC) | Searched | Sources | Latency |
|---|---|---|---|---|---|---|
| Direct recommendation | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 11:16 | no | 0 | 5 s |
| Direct recommendation | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 19:35 | yes | 5 | 6 s |
| Direct recommendation | Gemini 3.5 Flash | gemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version) | 2026-11-01 12:50 | no | 0 | 17 s |
| Direct recommendation | Perplexity Sonar | sonar | 2026-11-01 08:56 | yes | 10 | 4 s |
| Direct recommendation | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 16:42 | yes | 9 | 13 s |
| Direct recommendation | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 18:59 | yes | 5 | 4 s |
| Direct recommendation | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 10:37 | yes | 21 | 25 s |
| Direct recommendation | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 16:23 | yes | 5 | 3 s |
| Direct recommendation | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 08:36 | no | 0 | 27 s |
| Direct recommendation | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 19:35 | yes | 14 | 45 s |
| Direct recommendation | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 11:25 | yes | 24 | 114 s |
| Direct recommendation | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 10:32 | yes | 15 | 60 s |
| Direct recommendation | GPT-6 Luna | gpt-6-luna | 2026-11-01 16:23 | yes | 3 | 14 s |
| Direct recommendation | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 09:18 | yes | 14 | 21 s |
| Paraphrase | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 09:37 | no | 0 | 5 s |
| Paraphrase | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 09:04 | yes | 3 | 6 s |
| Paraphrase | Gemini 3.5 Flash | gemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version) | 2026-11-01 13:01 | no | 0 | 16 s |
| Paraphrase | Perplexity Sonar | sonar | 2026-11-01 17:00 | yes | 10 | 4 s |
| Paraphrase | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 13:55 | yes | 5 | 9 s |
| Paraphrase | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 09:44 | no | 0 | 7 s |
| Paraphrase | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 15:13 | yes | 24 | 39 s |
| Paraphrase | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 12:52 | yes | 5 | 3 s |
| Paraphrase | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 12:27 | yes | 5 | 23 s |
| Paraphrase | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 17:01 | yes | 20 | 22 s |
| Paraphrase | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 08:39 | yes | 15 | 91 s |
| Paraphrase | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 14:35 | yes | 15 | 30 s |
| Paraphrase | GPT-6 Luna | gpt-6-luna | 2026-11-01 14:57 | yes | 3 | 15 s |
| Paraphrase | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 11:56 | yes | 11 | 20 s |
| Comparative | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 14:37 | yes | 17 | 12 s |
| Comparative | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 12:57 | yes | 4 | 9 s |
| Comparative | Gemini 3.5 Flash | gemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version) | 2026-11-01 12:42 | no | 0 | 20 s |
| Comparative | Perplexity Sonar | sonar | 2026-11-01 11:13 | yes | 10 | 6 s |
| Comparative | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 18:27 | yes | 5 | 15 s |
| Comparative | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 13:28 | yes | 9 | 12 s |
| Comparative | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 19:33 | yes | 25 | 70 s |
| Comparative | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 15:50 | yes | 5 | 2 s |
| Comparative | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 16:02 | yes | 5 | 21 s |
| Comparative | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 13:26 | yes | 18 | 51 s |
| Comparative | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 08:54 | yes | 23 | 49 s |
| Comparative | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 19:41 | yes | 10 | 50 s |
| Comparative | GPT-6 Luna | gpt-6-luna | 2026-11-01 13:57 | yes | 8 | 26 s |
| Comparative | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 17:26 | yes | 14 | 26 s |
| Budget constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 09:27 | yes | 17 | 9 s |
| Budget constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 12:03 | yes | 3 | 5 s |
| Budget constrained | Gemini 3.5 Flash | gemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version) | 2026-11-01 10:27 | no | 0 | 20 s |
| Budget constrained | Perplexity Sonar | sonar | 2026-11-01 11:09 | yes | 10 | 4 s |
| Budget constrained | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 19:01 | yes | 5 | 9 s |
| Budget constrained | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 14:30 | yes | 5 | 4 s |
| Budget constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 18:14 | yes | 23 | 23 s |
| Budget constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 18:33 | yes | 5 | 3 s |
| Budget constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 13:02 | no | 0 | 32 s |
| Budget constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 14:49 | yes | 22 | 60 s |
| Budget constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 12:12 | yes | 24 | 24 s |
| Budget constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 15:01 | yes | 9 | 54 s |
| Budget constrained | GPT-6 Luna | gpt-6-luna | 2026-11-01 12:40 | yes | 4 | 13 s |
| Budget constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 13:26 | yes | 13 | 20 s |
| Scale constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 12:32 | yes | 17 | 9 s |
| Scale constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 16:31 | yes | 6 | 9 s |
| Scale constrained | Gemini 3.5 Flash | gemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version) | 2026-11-01 09:08 | no | 0 | 20 s |
| Scale constrained | Perplexity Sonar | sonar | 2026-11-01 14:36 | yes | 10 | 9 s |
| Scale constrained | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 15:22 | yes | 15 | 16 s |
| Scale constrained | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 14:33 | no | 0 | 5 s |
| Scale constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 14:56 | yes | 25 | 36 s |
| Scale constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 16:28 | yes | 5 | 3 s |
| Scale constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 10:44 | no | 0 | 33 s |
| Scale constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 17:07 | yes | 24 | 74 s |
| Scale constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 12:49 | yes | 24 | 48 s |
| Scale constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 14:31 | yes | 25 | 47 s |
| Scale constrained | GPT-6 Luna | gpt-6-luna | 2026-11-01 12:43 | yes | 4 | 25 s |
| Scale constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 10:14 | yes | 14 | 19 s |
| Negative framing | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 10:56 | yes | 19 | 9 s |
| Negative framing | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 17:43 | yes | 3 | 6 s |
| Negative framing | Gemini 3.5 Flash | gemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version) | 2026-11-01 13:00 | no | 0 | 19 s |
| Negative framing | Perplexity Sonar | sonar | 2026-11-01 18:13 | yes | 10 | 6 s |
| Negative framing | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 16:02 | yes | 15 | 19 s |
| Negative framing | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 15:27 | yes | 14 | 11 s |
| Negative framing | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 11:06 | yes | 25 | 59 s |
| Negative framing | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 19:43 | yes | 5 | 4 s |
| Negative framing | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 13:42 | yes | 22 | 58 s |
| Negative framing | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 13:01 | yes | 24 | 40 s |
| Negative framing | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 12:49 | yes | 14 | 53 s |
| Negative framing | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 17:14 | yes | 25 | 58 s |
| Negative framing | GPT-6 Luna | gpt-6-luna | 2026-11-01 17:38 | yes | 4 | 15 s |
| Negative framing | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 08:40 | yes | 23 | 30 s |
Normalization in this category
Every judgment call made between the raw labels and the numbers above, listed so it is visible and reversible.
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Category-scoped readings
AWS Timestream read as Amazon Timestream
Unresolved, counted raw
AVEVA
AWS Timestream LiveAnalytics
CrateDB Cloud
Elasticsearch with time series support
Epsilon3
InfluxDB 1.x / 2.x Open Source (OSS)
InfluxDB Cloud Dedicated or Enterprise
InfluxDB v1.x
KX kdb+ / KDB‑X
OSI PI
OSIsoft PI
RDS PostgreSQL
Wonderware
Discontinued, still offered
No shut-down product was recommended here.