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. 59 first choices recorded across the direct, paraphrase, budget and scale prompts, fourteen models each. Added to the October 2026 Edition on October 4, 2026; its answers are read by the distilled judge (ai-indexes-judge-qwen3-14b-run3), not the claude-opus-5 judge of the earlier categories: how the two compare.
Standing · first-choice share
47%
Clear leader
47TimescaleDB17InfluxDB15VictoriaMetrics20others
47% of first choices, clear leader.
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.
The 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 rateLabelsQuadrant
Show the four products at 0%, ordered by negative rate
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.
All fifteen head-to-head pages: the top six products, each against each
Recommended versus criticized
Every product with at least 10 labels here, on both axes. The 30% line names a quadrant, not the verdict above: that one needs more than 40%.
Criticized challengerCriticized default
Negative label rate →
01
02
03
04A05
I06
07
08
09O10
Accepted challengerEndorsed leader
0%First-choice share → · lines at 30% share and 25% negative60%
Key
01TimescaleDB47%
TimescaleDB47%02InfluxDB17%
InfluxDB17%03VictoriaMetrics15%
VictoriaMetrics15%04QuestDB8%
QuestDB8%05Amazon Timestream3%
06InfluxDB 3 Enterprise3%
07ClickHouse Cloud0%
ClickHouse Cloud0%08Thanos0%
Thanos0%09Prometheus0%
Prometheus0%10OpenTSDB0%
What they warned about
Six of fourteen models held their first choice under the paraphrase. GPT-5.4 mini, Mistral Small, DeepSeek V4 Flash, Llama 4 Maverick, Qwen 3.7 Flash, MiniMax M2.5, GPT-6 Luna and Muse Glimmer 30B 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.
InfluxDB23%
14 of 62 labels negative · 12 of 14 models · 3 hard negative
“avoiding per-user pricing like the InfluxDB $25/user/month starting price shown in current lists” Muse Glimmer 30B, budget prompt
Prometheus47%
14 of 30 labels negative · 10 of 14 models · 6 hard negative
“it's often best to avoid relying on Prometheus or older InfluxDB versions as your primary TSDB at scale” Mistral Small, negative prompt
OpenTSDB
90%
9 of 10 labels negative · 9 of 14 models · 6 hard negative
“depends on **HBase** underneath and introduces added operational overhead because the query layer is effectively separate” Perplexity Sonar, negative prompt
PostgreSQL100%
7 of 7 labels negative · 7 of 14 models · 2 hard negative
“Not designed for time series: Performance degrades significantly beyond tens of millions of rows” MiniMax M2.5, negative prompt
What they cite
Citations exist only for the models that return a source list: fourteen of the fourteen in this edition, and all six flagship models on the expanded tier.
Sites the answers cite
78 of 84 answers in this category came back with a source list, from 14 of 14 models: citations where the model returns them, or the search results it consulted. 1071 links across 200 sites, every framing counted. Ranked by the number of answers carrying the site or page. None of the 252 answers across every segment cited this index's own page for the category.
vendor site · TigerData60 answers · 120 citations · 12 models
vendor site · Guideflow52 answers · 53 citations · 12 models
vendor site · QuestDB43 answers · 53 citations · 14 models
vendor site · InfluxData42 answers · 84 citations · 13 models
35 answers · 35 citations · 10 models
vendor site · SourceForge28 answers · 41 citations · 11 models
26 answers · 33 citations · 10 models
25 answers · 32 citations · 11 models
vendor site · Amazon21 answers · 49 citations · 11 models
vendor site · FitGap21 answers · 37 citations · 11 models
vendor site · InfluxData21 answers · 32 citations · 8 models
12 answers · 15 citations · 7 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.
51 answers · 12 models
46 answers · 12 models
35 answers · 10 models
34 answers · 12 models
21 answers · 10 models
21 answers · 10 models
20 answers · 9 models
19 answers · 11 models
18 answers · 10 models
16 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 |
|---|---|---|---|---|---|---|---|---|
| TigerData tigerdata.com TimescaleDB 47%, TigerData 0% | 47% | 183 | 3,600 | 147 | 23,549 | $658 | 27 | 2 |
| InfluxDB influxdata.com | 17% | 176 | 4,400 | 350 | 46,684 | 44 | 3 | |
| VictoriaMetrics victoriametrics.com | 15% | 107 | 1,300 | 52 | 4,097 | 0 | 6 | |
| QuestDB questdb.com | 8% | 142 | 880 | 6 | 14,289 | 2 | 4 | |
| Amazon parent site Amazon Timestream 3%, Amazon Timestream for InfluxDB 0% | 3% | 65 | 151,000,000 | 1,380,939 | ||||
| InfluxDB 3 Enterprise | 3% | 30 | 0 | |||||
| Timescale Cloud timescale.com | 2% | 8 | 90 | 0 | 93 | |||
| TimescaleDB Cloud | 2% | |||||||
| Datadog datadoghq.com | 2% | 585 | 74,000 | 3,541 | 159,408 | $633 | 120 | |
| ClickHouse Cloud clickhouse.com | 0% | 178 | 1,000 | 15 | 43,805 | 47 |
Google's top ten for the three searches hold 24 sites; 4 of them are among the sites the models cited here (aws.amazon.com, influxdata.com, questdb.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, TimescaleDBInfluxDB, TimescaleDBHeldno first choiceTimescaleDBno first choiceagainst: ClickHouse Cloud, InfluxDB, OpenTSDB, Prometheus
One alternative
CrateDBTwo alternatives
InfluxDB Cloud Dedicated or Enterprise, VictoriaMetricsGPT-5.4 miniTimescaleDBInfluxDB 3 EnterpriseChangedAmazon Timestream, InfluxDB, InfluxDB 3 Enterpriseagainst: OpenTSDBTimescaleDBagainst: ClickHouse Cloud, InfluxDBTimescale Cloudagainst: Graphite, InfluxDB 3 Core, TimescaleDB Community Edition / self-managed TimescaleDB
Four alternatives
Apache Druid, ClickHouse Cloud, InfluxDB 3 Enterprise, QuestDBTwo alternatives
ClickHouse Cloud, TimescaleDBFour alternatives
Apache Druid, Apache Pinot, ClickHouse Cloud, TimescaleDBOne alternative
InfluxDB 3 EnterpriseTwo alternatives
InfluxDB, QuestDBGemini 3.5 FlashTimescaleDBTimescaleDBHeldagainst: Amazon Timestreamno first choiceVictoriaMetricsagainst: Amazon Timestream, Google BigQueryTimescaleDBagainst: Apache Cassandra, Apache HBase, Elasticsearch, Graphite, InfluxDB, OpenSearch, OpenTSDB, RRDtool, ScyllaDB, TimescaleDB, vanilla Prometheus
Two alternatives
ClickHouse Cloud, InfluxDBThree alternatives
Azure Data Explorer, ClickHouse Cloud, InfluxDBFive alternatives
ClickHouse Cloud, InfluxDB, QuestDB, TimescaleDB, VictoriaMetricsTwo alternatives
ClickHouse Cloud, TimescaleDBFive alternatives
Amazon Timestream, Azure Data Explorer, ClickHouse Cloud, Google Cloud Bigtable, InfluxDBPerplexity SonarTimescaleDBTimescaleDBHeldTimescaleDBVictoriaMetricsQuestDBagainst: Apache Cassandra, MongoDB, MySQL, OpenTSDB, PostgreSQL
Two alternatives
InfluxDB, QuestDBTwo alternatives
Amazon Timestream, InfluxDBSix alternatives
Amazon Timestream, Apache Druid, InfluxDB, QuestDB, TDengine, VictoriaMetricsThree alternatives
Amazon Timestream, TigerData, Timescale CloudOne alternative
Amazon TimestreamGrok 4.1 FastInfluxDBInfluxDBHeldagainst: ClickHouse Cloud, Prometheus, QuestDBInfluxDBTimescaleDB, VictoriaMetricsagainst: Amazon Timestream, ClickHouse Cloud, InfluxDBInfluxDB, QuestDB, TimescaleDBagainst: CrateDB, Graphite, InfluxDB, MySQL, OpenTSDB, PostgreSQL, Prometheus, QuestDB, VictoriaMetrics
Three alternatives
Amazon Timestream, Prometheus, TimescaleDBOne alternative
TimescaleDBSeven alternatives
Amazon Timestream, ClickHouse Cloud, Prometheus, QuestDB, TDengine, TigerData, TimescaleDBOne alternative
Amazon TimestreamMistral SmallQuestDB, TimescaleDBTimescaleDBChangedagainst: MongoDBInfluxDBno first choiceno first choiceagainst: InfluxDB, Prometheus, TDengine, TimescaleDB
One alternative
Amazon TimestreamTwo alternatives
ClickHouse Cloud, InfluxDBFive alternatives
Amazon Timestream, Prometheus, QuestDB, TimescaleDB, VictoriaMetricsTwo alternatives
QuestDB, TimescaleDBDeepSeek V4 FlashInfluxDB, TimescaleDBVictoriaMetricsChangedagainst: Amazon Timestream, Datadog, InfluxDB, Prometheusno first choiceagainst: kdb+TimescaleDBagainst: InfluxDB 3 Enterpriseno first choiceagainst: TimescaleDBagainst: Elasticsearch, Graphite, InfluxDB, KairosDB, MongoDB, OpenTSDB, PostgreSQL, Prometheus, RRDtool
Three alternatives
Amazon Timestream, ClickHouse Cloud, PrometheusTwo alternatives
ClickHouse Cloud, TimescaleDBFive alternatives
Amazon Timestream, InfluxDB, QuestDB, TimescaleDB, VictoriaMetricsTwo alternatives
Amazon Timestream for InfluxDB, VictoriaMetricsLlama 4 MaverickQuestDBno first choiceChangedno first choiceAmazon Timestream, TimescaleDBno first choicenothing named
Qwen 3.7 FlashTimescaleDBInfluxDBChangedagainst: MySQL, PostgreSQLInfluxDBVictoriaMetricsDatadogagainst: InfluxData, Promtail + Lokiagainst: InfluxDB, KairosDB, Prometheus, RethinkDB, Splunk Observability Cloud
Six alternatives
Amazon Timestream, Azure Data Explorer, Google Cloud Monitoring, InfluxDB, KX, VictoriaMetricsFour alternatives
Amazon Timestream, Azure Data Explorer, TimescaleDB, VictoriaMetricsTwo alternatives
QuestDB, TimescaleDBTwo alternatives
TDengine, TimescaleDBTwo alternatives
New Relic, TimescaleDBKimi K2TimescaleDBTimescaleDBHeldInfluxDB, TimescaleDBagainst: Apache DruidTimescaleDBagainst: Amazon Timestream, InfluxDB Cloud Serverless, PrometheusTimescaleDB Cloudagainst: Amazon Timestream, Mimir OSS, Thanos, vanilla Prometheusagainst: InfluxDB, OpenTSDB, Prometheus
One alternative
InfluxDBThree alternatives
ClickHouse Cloud, InfluxDB, VictoriaMetricsFour alternatives
Amazon Timestream, ClickHouse Cloud, Prometheus, QuestDBOne alternative
InfluxDB 3 EnterpriseTwo alternatives
Grafana Enterprise Metrics, InfluxDB Cloud Serverless / InfluxDB 3 EnterpriseGLM 4.7 FlashXTimescaleDBTimescaleDBHeldTimescaleDBagainst: PrometheusVictoriaMetricsno first choiceagainst: Apache Cassandra, InfluxDB, MongoDB, MySQL, Oracle, PostgreSQL, Prometheus
Three alternatives
ClickHouse Cloud, InfluxDB 3 Enterprise, VictoriaMetricsOne alternative
InfluxDBFive alternatives
Amazon Timestream, ClickHouse Cloud, InfluxDB, QuestDB, VictoriaMetricsTwo alternatives
InfluxDB, TimescaleDBMiniMax M2.5no first choiceagainst: kdb+Amazon Timestream, InfluxDBChangedno first choiceTimescaleDB, VictoriaMetricsInfluxDB, QuestDBagainst: ClickHouse Cloudagainst: Graphite, InfluxDB, MySQL, OpenTSDB, Oracle, PostgreSQL, Prometheus, RRDtool
Two alternatives
Google Cloud Bigtable, TimescaleDBThree alternatives
Amazon Timestream, InfluxDB, QuestDBTwo alternatives
Amazon Timestream, TimescaleDBGPT-6 LunaTimescaleDBInfluxDB 3 EnterpriseChangedno first choiceVictoriaMetricsno first choiceagainst: Amazon Timestream for LiveAnalytics, InfluxDB, InfluxDB 1.x or 2.x, OpenTSDB, Prometheus, TimescaleDB
Three alternatives
ClickHouse Cloud, InfluxDB, VictoriaMetricsFour alternatives
ClickHouse Cloud, Grafana Mimir, TimescaleDB, VictoriaMetricsSix alternatives
Amazon Timestream for LiveAnalytics, ClickHouse Cloud, InfluxDB 3 Enterprise, QuestDB, TimescaleDB, VictoriaMetricsOne alternative
InfluxDB Cloud DedicatedFour alternatives
Amazon Timestream for InfluxDB, ClickHouse Cloud or BYOC, InfluxDB Cloud Dedicated, Timescale CloudMuse Glimmer 30BInfluxDB, TimescaleDBTimescaleDBChangedInfluxDB, QuestDBTimescaleDB, VictoriaMetricsagainst: InfluxDBno first choiceagainst: InfluxDB 3 Enterprise, MySQL, PostgreSQL, Prometheus
One alternative
QuestDBTwo alternatives
InfluxDB, QuestDBFour alternatives
Amazon Timestream, Google Cloud Bigtable, TDengine, TimescaleDB – now Tiger DataTwo alternatives
Prometheus, QuestDBBold 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. Full answer text is in the free responses file. Download the record
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 | 2026-10-05 01:24 | yes | 17 | 9 s |
| Direct recommendation | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-04 23:37 | yes | 4 | 6 s |
| Direct recommendation | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-05 00:41 | yes | 14 | 28 s |
| Direct recommendation | Perplexity Sonar | sonar | 2026-10-05 00:35 | yes | 18 | 3 s |
| Direct recommendation | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-05 00:55 | yes | 19 | 11 s |
| Direct recommendation | Mistral Small | mistral/mistral-small via mistral | 2026-10-05 01:52 | yes | 10 | 6 s |
| Direct recommendation | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-05 01:33 | yes | 16 | 34 s |
| Direct recommendation | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-05 01:27 | yes | 5 | 2 s |
| Direct recommendation | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-05 01:42 | no | 0 | 31 s |
| Direct recommendation | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-04 23:37 | yes | 19 | 55 s |
| Direct recommendation | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-05 01:25 | yes | 24 | 209 s |
| Direct recommendation | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-05 01:35 | yes | 7 | 37 s |
| Direct recommendation | GPT-6 Luna | gpt-6-luna | 2026-10-05 00:39 | yes | 4 | 15 s |
| Direct recommendation | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-04 23:58 | yes | 11 | 16 s |
| Paraphrase | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-05 01:50 | no | 0 | 5 s |
| Paraphrase | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-05 00:50 | yes | 2 | 4 s |
| Paraphrase | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-05 00:36 | no | 0 | 16 s |
| Paraphrase | Perplexity Sonar | sonar | 2026-10-05 00:25 | yes | 18 | 3 s |
| Paraphrase | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-05 01:24 | yes | 14 | 8 s |
| Paraphrase | Mistral Small | mistral/mistral-small via mistral | 2026-10-05 01:47 | no | 0 | 7 s |
| Paraphrase | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-05 00:19 | yes | 17 | 43 s |
| Paraphrase | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-05 00:18 | yes | 5 | 2 s |
| Paraphrase | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-05 01:32 | yes | 10 | 34 s |
| Paraphrase | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-05 01:34 | yes | 7 | 41 s |
| Paraphrase | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-05 00:00 | yes | 12 | 50 s |
| Paraphrase | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-04 22:46 | yes | 13 | 64 s |
| Paraphrase | GPT-6 Luna | gpt-6-luna | 2026-10-05 01:15 | yes | 4 | 16 s |
| Paraphrase | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-04 22:58 | yes | 14 | 28 s |
| Comparative | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-05 00:43 | yes | 9 | 9 s |
| Comparative | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-04 23:39 | yes | 3 | 10 s |
| Comparative | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-05 01:24 | yes | 27 | 32 s |
| Comparative | Perplexity Sonar | sonar | 2026-10-05 01:38 | yes | 17 | 4 s |
| Comparative | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-05 00:19 | yes | 20 | 11 s |
| Comparative | Mistral Small | mistral/mistral-small via mistral | 2026-10-04 23:51 | yes | 15 | 13 s |
| Comparative | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-04 23:53 | yes | 23 | 43 s |
| Comparative | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-05 01:54 | yes | 5 | 2 s |
| Comparative | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-05 00:18 | yes | 8 | 26 s |
| Comparative | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-04 23:23 | yes | 23 | 70 s |
| Comparative | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-05 01:38 | yes | 22 | 56 s |
| Comparative | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-04 23:56 | yes | 5 | 18 s |
| Comparative | GPT-6 Luna | gpt-6-luna | 2026-10-05 00:02 | yes | 10 | 25 s |
| Comparative | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-04 23:34 | yes | 11 | 27 s |
| Budget constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-04 22:18 | yes | 15 | 9 s |
| Budget constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-05 01:44 | yes | 5 | 5 s |
| Budget constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-05 00:14 | yes | 20 | 29 s |
| Budget constrained | Perplexity Sonar | sonar | 2026-10-04 23:25 | yes | 18 | 4 s |
| Budget constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-04 23:59 | yes | 19 | 19 s |
| Budget constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-04 23:10 | yes | 5 | 5 s |
| Budget constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-05 01:37 | yes | 21 | 29 s |
| Budget constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-05 00:28 | yes | 5 | 2 s |
| Budget constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-04 22:29 | yes | 10 | 35 s |
| Budget constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-04 22:48 | yes | 21 | 78 s |
| Budget constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-05 01:29 | yes | 20 | 17 s |
| Budget constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-04 23:56 | yes | 20 | 60 s |
| Budget constrained | GPT-6 Luna | gpt-6-luna | 2026-10-04 22:15 | yes | 2 | 15 s |
| Budget constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-04 22:55 | yes | 12 | 30 s |
| Scale constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-05 00:39 | yes | 18 | 12 s |
| Scale constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-05 00:31 | yes | 4 | 7 s |
| Scale constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-04 22:35 | yes | 20 | 31 s |
| Scale constrained | Perplexity Sonar | sonar | 2026-10-04 23:45 | yes | 20 | 5 s |
| Scale constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-05 01:26 | yes | 17 | 10 s |
| Scale constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-04 23:42 | no | 0 | 8 s |
| Scale constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-04 23:08 | yes | 25 | 38 s |
| Scale constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-04 23:51 | yes | 5 | 3 s |
| Scale constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-04 22:39 | no | 0 | 25 s |
| Scale constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-05 00:58 | yes | 25 | 39 s |
| Scale constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-05 01:11 | yes | 23 | 47 s |
| Scale constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-05 00:48 | yes | 5 | 48 s |
| Scale constrained | GPT-6 Luna | gpt-6-luna | 2026-10-04 23:38 | yes | 4 | 24 s |
| Scale constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-05 01:00 | yes | 14 | 19 s |
| Negative framing | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-05 00:15 | yes | 17 | 9 s |
| Negative framing | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-05 00:15 | yes | 4 | 8 s |
| Negative framing | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-05 01:28 | yes | 6 | 27 s |
| Negative framing | Perplexity Sonar | sonar | 2026-10-05 01:32 | yes | 19 | 5 s |
| Negative framing | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-04 22:42 | yes | 19 | 11 s |
| Negative framing | Mistral Small | mistral/mistral-small via mistral | 2026-10-04 22:10 | yes | 18 | 13 s |
| Negative framing | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-05 01:33 | yes | 25 | 78 s |
| Negative framing | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-04 22:44 | yes | 5 | 2 s |
| Negative framing | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-05 01:56 | yes | 10 | 51 s |
| Negative framing | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-04 22:42 | yes | 24 | 26 s |
| Negative framing | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-05 01:57 | yes | 22 | 164 s |
| Negative framing | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-05 00:17 | yes | 21 | 60 s |
| Negative framing | GPT-6 Luna | gpt-6-luna | 2026-10-05 00:15 | yes | 5 | 23 s |
| Negative framing | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-05 00:39 | yes | 21 | 35 s |
Normalization in this category
Every judgment call made between the raw labels and the numbers above, listed so it is visible and reversible.
ShowHide
Category-scoped readings
AWS Timestream read as Amazon Timestream
Unresolved, counted raw
Amazon Managed Prometheus
ClickHouse Cloud or BYOC
Cognite Data Fusion
DataStax Astra
Google's BigQuery
Grafana Enterprise Metrics (GEM)
InfluxDB Cloud Dedicated or Enterprise
InfluxDB Cloud Serverless
InfluxDB Cloud Serverless / InfluxDB 3 Enterprise
Mimir OSS
Promtail + Loki
Riak TS
TimescaleDB Cloud (Enterprise Tier)
TimescaleDB Community Edition / self-managed TimescaleDB
TimescaleDB – now Tiger Data
Discontinued, still offered
No shut-down product was recommended here.