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November 2026 Edition · The permanent record of this edition. The unqualified address always carries the latest edition.
Index › IT › Data platform › NoSQL · November 2026 Edition

NoSQL databases

Asked as “NoSQL database”, and as “document or key-value database service”, on behalf of a mid-market B2B company. 57 first choices recorded across the direct, paraphrase, budget and scale prompts, fourteen models each.
Standing · first-choice share
74%
MongoDB
Clear leader
74MongoDB12Amazon DynamoDB04PostgreSQL11others

74% of first choices, clear leader.

Since October 2026=heldSince October 2026: 74% → 74%, ±0 points. Inside the 11-point floor: within noise.MongoDB held the lead, ±0 points on 74%, inside the 11-point floor.
ShowinginAll 136 categories in the November 2026 Edition →

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 businessMongoDB81%Clear leader▲+12Since October 2026: 69% → 81%, +12 points. Past the 11-point floor: movement.Standing →Mid-marketMongoDB74%Clear leader=heldSince October 2026: 74% → 74%, ±0 points. Inside the 11-point floor: within noise.This pageEnterpriseMongoDB53%Clear leader▼−3Since October 2026: 56% → 53%, −3 points. Inside the 11-point floor: within noise.Standing →

The standing

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. Ordered by share.
ProductFirst-choice shareNegative rateLabelsQuadrantSince October 2026
01MongoDB74%11%82endorsed leader=heldSince October 2026: 74% → 74%, ±0 points. Inside the 11-point floor: within noise.74% → 74%
02Amazon DynamoDB12%17%65accepted challenger▲+1Since October 2026: 11% → 12%, +1 point. Inside the 11-point floor: within noise.11% → 12%
03PostgreSQL4%0%13accepted challenger▲+2Since October 2026: 2% → 4%, +2 points. Inside the 11-point floor: within noise.2% → 4%
04Redis2%21%56accepted challenger=heldSince October 2026: 2% → 2%, ±0 points. Inside the 11-point floor: within noise.2% → 2%
05Apache Cassandra2%31%54criticized challenger▲+2Since October 2026: 0% → 2%, +2 points. Inside the 11-point floor: within noise.0% → 2%
06Azure Cosmos DB2%25%24criticized challenger▲+2Since October 2026: 0% → 2%, +2 points. Inside the 11-point floor: within noise.0% → 2%
07Apache CouchDB2%42%12criticized challenger▲+2Since October 2026: 0% → 2%, +2 points. Inside the 11-point floor: within noise.0% → 2%
Show the seven products at 0%, ordered by negative rate
14Apache HBase0%42%19criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%
13Elasticsearch0%33%12criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%
12Google Cloud Firestore Lab in the set0%25%16criticized challenger▼−2Since October 2026: 2% → 0%, −2 points. Inside the 11-point floor: within noise.2% → 0%
08Couchbase0%16%44accepted challenger▼−4Since October 2026: 4% → 0%, −4 points. Inside the 11-point floor: within noise.4% → 0%
11Amazon DocumentDB0%15%13accepted challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%
09Neo4j0%9%32accepted challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%
10ScyllaDB0%5%20accepted challenger▼−2Since October 2026: 2% → 0%, −2 points. Inside the 11-point floor: within noise.2% → 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.

Google Cloud Firestore is made by Google, whose model Gemini 3.5 Flash is in the set. On the four share prompts that model made it the first choice zero times of 4; the other thirteen models zero times of 52. Lab treatment is defined on the method page; the row is marked, not excluded.

Head to head
MongoDB vs Amazon DynamoDBMongoDB vs PostgreSQLMongoDB vs Redis
All twenty-one head-to-head pages: the top seven products, each against each
MongoDB vs Apache CassandraMongoDB vs Azure Cosmos DBMongoDB vs Apache CouchDBAmazon DynamoDB vs PostgreSQLAmazon DynamoDB vs RedisAmazon DynamoDB vs Apache CassandraAmazon DynamoDB vs Azure Cosmos DBAmazon DynamoDB vs Apache CouchDBPostgreSQL vs RedisPostgreSQL vs Apache CassandraPostgreSQL vs Azure Cosmos DBPostgreSQL vs Apache CouchDBRedis vs Apache CassandraRedis vs Azure Cosmos DBRedis vs Apache CouchDBApache Cassandra vs Azure Cosmos DBApache Cassandra vs Apache CouchDBAzure Cosmos DB vs Apache CouchDB

One product takes 74% of first choices here, so the chart would put thirteen 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

Seven 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, Mistral Small, Llama 4 Maverick and GLM 4.7 FlashX 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.
Apache Cassandra
31%
17 of 54 labels negative · 12 of 14 models · 3 hard negative
“Verdict: Avoid unless you have a team of Cassandra specialists and a use case that truly demands it.” Kimi K2, negative prompt
Redis
21%
12 of 56 labels negative · 10 of 14 models · 1 hard negative
“Avoid Redis as a sole data store for critical financial data.” MiniMax M2.5, negative prompt
Amazon DynamoDB
17%
11 of 65 labels negative · 9 of 14 models · 2 hard negative
“AI models and experts often advise avoiding DynamoDB as a primary application database unless your use case is a perfect fit for key-value patterns.” Mistral Small, negative prompt
MongoDB
11%
9 of 82 labels negative · 8 of 14 models · 1 hard negative
“Avoid MongoDB if you need multi-document ACID transactions” MiniMax M2.5, negative 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

60 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. 612 links across 208 sites, every framing counted. Ranked by the number of answers carrying the site or page. 54 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.

mongodb.com
vendor site · MongoDB19 answers · 31 citations · 9 models
docs.aws.amazon.com
vendor site · Amazon17 answers · 23 citations · 8 models
couchbase.com
vendor site · Couchbase16 answers · 25 citations · 7 models
aws.amazon.com
vendor site · Amazon16 answers · 22 citations · 9 models
github.com
vendor site · GitHub15 answers · 20 citations · 9 models
g2.com
vendor site · G213 answers · 16 citations · 9 models
aerospike.com
vendor site · Aerospike11 answers · 14 citations · 6 models
capterra.com
11 answers · 11 citations · 7 models
gane.ai/index
publisher (Gane)11 answers · 11 citations · 6 models
sourceforge.net
vendor site · SourceForge9 answers · 10 citations · 7 models
db-engines.com
8 answers · 11 citations · 7 models
linkedin.com
vendor site · LinkedIn8 answers · 11 citations · 4 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.

github.com/quanpan302/KB-engineering-handbook/blob/main/content/hld/part-2-…
13 answers · 8 models
aws.amazon.com/nosql
11 answers · 6 models
gane.ai/index/it/it-data/nosql-databases
10 answers · 5 models
aerospike.com/blog/ten-best-nosql-cloud-databases
9 answers · 5 models
capterra.com/nosql-databases-software
9 answers · 7 models
em360tech.com/top-10/best-nosql-databases
8 answers · 6 models
g2.com/categories/nosql-databases
7 answers · 7 models
guideflow.com/blog/nosql-database-software
7 answers · 5 models
instaclustr.com/education/nosql-database/nosql-databases-types-use-cases-an…
7 answers · 4 models
thectoclub.com/tools/best-nosql-database
7 answers · 5 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 nosql database”, “nosql database”, “nosql 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 productsShareOwn site citedName searches, GoogleAI search demand, est.Organic visitsPaid search a month, est.Google ads, last 30 daysBest Google position
MongoDB mongodb.com74%17774,0009,630342,632$8,6251201
Amazon aws.amazon.com
Amazon DynamoDB 12%		12%154151,000,0001,380,9399,238,321$20,4765
PostgreSQL postgresql.org4%7774,00014,143465,585
Apache CouchDB apache.org
Apache Cassandra 2%, Apache CouchDB 2%		4%1241,60041,144,0250
Redis redis.io2%10727,1006,980112,42418
Azure parent site
Azure Cosmos DB 2%		2%76301,00047,904
Firebase firebase.google.com2%690,5003,43791,247
Atlas2%
Couchbase couchbase.com0%854,40022162,564$3426
Neo4j neo4j.com0%4818,1001,08644,57697

Google's top ten for the three searches hold 14 sites; 3 of them are among the sites the models cited here (aerospike.com, aws.amazon.com, mongodb.com). The first result for “best nosql 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
ModelDirect“What is the best NoSQL database for a mid-market B2B company?”Paraphrase“Which document or key-value database service would you recommend to a mid-sized B2B company?”Comparative“What are the top NoSQL databases and how do they differ?”Budget-constrained“What is the best NoSQL database for a company with a limited budget?”Scale-constrained“We are a 500 person company evaluating a NoSQL database. What should we look at?”Negative“Which NoSQL databases should I avoid or be cautious about?”
Claude Haiku 4.5Amazon DynamoDB, MongoDB
Two alternativesFirebase, Redis
MongoDBChanged
Two alternativesGoogle Cloud Firestore, Redis
no first choiceMongoDB
Four alternativesAmazon DynamoDB, Apache CouchDB, Firebase, Redis
no first choicenothing named
GPT-5.4 miniAmazon DynamoDB, MongoDB
One alternativeAzure Cosmos DB
MongoDBChanged
Three alternativesAmazon DynamoDB, Azure Cosmos DB, Google Cloud Firestore
no first choiceMongoDB, PostgreSQL
One alternativeRedis
against: Apache Cassandrano first choiceagainst: Amazon DynamoDB, Apache Cassandra, Redis
Gemini 3.5 FlashMongoDB
Five alternativesAmazon DynamoDB, Azure Cosmos DB, Couchbase, Neo4j, Redis
Amazon DynamoDB, MongoDBChanged
Six alternativesAWS ElastiCache for Redis/Valkey, Amazon DocumentDB, Azure Cosmos DB, Couchbase, Managed Redis / Valkey, Redis
MongoDB
Five alternativesAmazon DynamoDB, Apache Cassandra, Couchbase, Neo4j, Redis
PostgreSQL
Four alternativesAmazon DynamoDB, Google Cloud Firestore, MongoDB, ScyllaDB
MongoDB
Eight alternativesAmazon DynamoDB, Apache Cassandra, ArangoDB, Azure Cosmos DB, Couchbase, Dragonfly, Redis, ScyllaDB
against: Amazon DynamoDB, Apache Cassandra, Apache HBase, Elasticsearch, Memcached, OrientDB, Project Voldemort, Redis, RethinkDB, Riak KV
Perplexity SonarMongoDB
Six alternativesAmazon DynamoDB, Apache Cassandra, Azure Cosmos DB, Couchbase, Neo4j, ScyllaDB
MongoDBHeld
Four alternativesAmazon DynamoDB, Couchbase, Google Cloud Firestore, Redis
MongoDB
Seven alternativesAmazon DynamoDB, Apache Cassandra, Azure Cosmos DB, Couchbase, Neo4j, Redis, ScyllaDB
MongoDB
Two alternativesAmazon DynamoDB, PostgreSQL
against: Apache Cassandra, Redis, ScyllaDBno first choiceagainst: Apache Cassandra, MongoDB
Grok 4.20MongoDB
Four alternativesAmazon DynamoDB, Apache Cassandra, Couchbase, Elasticsearch
against: Neo4j, Oracle NoSQL Database, RedisAmazon DynamoDB, MongoDBChanged
Four alternativesAerospike, Couchbase, Dragonfly, PostgreSQL
against: Redisno first choiceMongoDB
Six alternativesApache Cassandra, Elasticsearch, Neo4j Community Edition, Percona Server for MongoDB, PostgreSQL, Redis
against: Aerospike, Amazon DynamoDB, Azure Cosmos DB, Couchbase, MongoDBno first choice
Seven alternativesAmazon DynamoDB, Apache Cassandra, Azure Cosmos DB, Couchbase, MongoDB, Redis, ScyllaDB
against: Amazon DynamoDB, Apache Cassandra, Apache CouchDB, Apache HBase, Couchbase, MongoDB, Neo4j, Redis
Mistral SmallMongoDB
One alternativeAmazon DynamoDB
Amazon DynamoDB, MongoDBChangedno first choiceMongoDB
Two alternativesAmazon DynamoDB, IBM Cloudant
against: Apache Cassandra, Apache HBaseno first choice
Two alternativesMongoDB, ScyllaDB
against: Amazon DynamoDB, Apache Cassandraagainst: Amazon DynamoDB, Apache Cassandra, Apache HBase, MongoDB
DeepSeek V4 FlashMongoDB
Four alternativesAmazon DynamoDB, Apache Cassandra, Couchbase, DataStax
MongoDBHeld
Two alternativesAmazon DynamoDB, Redis
against: CouchbaseMongoDB
Five alternativesAmazon DynamoDB, Apache Cassandra, Couchbase, Neo4j, Redis
MongoDB
Five alternativesApache Cassandra, Apache CouchDB, Azure Cosmos DB, Google Cloud Firestore, Redis
no first choiceagainst: Amazon DynamoDB, Apache Cassandra, Apache CouchDB, Apache HBase, Couchbase, Fauna, Firebase Realtime Database, Google Cloud Firestore, KuzuDB, MongoDB, OrientDB, Redis, Riak KV
Llama 4 MaverickMongoDBno first choiceChangedno first choiceMongoDB
Four alternativesAmazon DynamoDB, Apache Cassandra, Couchbase, Redis
no first choicenothing named
Qwen 3.7 FlashMongoDB
Two alternativesAmazon DynamoDB, PostgreSQL
against: RedisMongoDBHeld
Three alternativesAmazon DynamoDB, PostgreSQL, Redis
MongoDB
Five alternativesAerospike, Amazon DynamoDB, Azure Cosmos DB, Couchbase, Redis
against: ElasticsearchFirebase, MongoDB
One alternativeRedis
against: Apache CassandraAmazon DynamoDB, Azure Cosmos DB
Two alternativesCockroachDB, MongoDB
against: Amazon DynamoDB, Amazon SimpleDB, Apache Cassandra, Apache HBase, Elasticsearch, Firebase, Google Cloud Firestore, InfluxDB, MongoDB, OrientDB, RethinkDB
Kimi K2MongoDB
Four alternativesAmazon DynamoDB, Apache Cassandra, Couchbase, Redis
MongoDBHeld
Two alternativesAmazon DynamoDB, Azure Cosmos DB
MongoDB
Four alternativesApache Cassandra, Elasticsearch, Neo4j, Redis
MongoDB
Three alternativesApache Cassandra, Redis, ScyllaDB
MongoDB
Six alternativesAmazon ElastiCache, Apache Cassandra, Couchbase, Neo4j, Redis, ScyllaDB
against: Amazon DynamoDB, Azure Cosmos DBagainst: 3store / 4store, ActorDB, AgateDB, AnuDB, Apache Cassandra, Apache HBase, AverageDB, CloverDB, Couchbase, CurioDB, DataStax, Elasticsearch, Isar, MongoDB, Redis
GLM 4.7 FlashXMongoDB
Four alternativesAmazon DynamoDB, Apache Cassandra, Azure Cosmos DB, Couchbase
MongoDB, RedisChanged
Three alternativesAmazon DocumentDB, Amazon DynamoDB, Azure Cosmos DB
against: Couchbaseno first choiceMongoDB
Two alternativesCouchbase Community Edition, Redis
against: AWS Astra, Amazon DynamoDB, Apache Cassandra, Apache HBase, Azure Cosmos DB, Google Cloud Spannerno first choiceagainst: Apache CouchDB, BoltDB, CloverDB, Couchbase, DataStax Astra DB, Oracle NoSQL Database, PNUTS, PouchDB, Riak KV
MiniMax M2.5MongoDB
Three alternativesApache Cassandra, Elasticsearch, Neo4j
MongoDBHeld
Two alternativesAmazon DynamoDB, Redis
no first choiceno first choiceAmazon DynamoDB, Atlas, MongoDB
Five alternativesAmazon ElastiCache, Apache Cassandra, DataStax Astra DB, Redis, ScyllaDB
against: Azure Cosmos DBagainst: Apache Cassandra, Apache CouchDB, MongoDB, Redis
GPT-6 LunaMongoDB
Two alternativesAmazon DynamoDB, Couchbase
MongoDBHeld
One alternativeAmazon DynamoDB
no first choiceMongoDB
Two alternativesAmazon DynamoDB, PostgreSQL
against: Atlasno first choiceagainst: Amazon DocumentDB, Apache Cassandra, Azure Cosmos DB, Google Cloud Firestore, Redis
Muse Glimmer 30BMongoDB
One alternativeAmazon DynamoDB
MongoDBHeld
Five alternativesAmazon DocumentDB, Amazon DynamoDB, Azure Cosmos DB, Couchbase, Google Cloud Firestore
Couchbase, MongoDB
Four alternativesAmazon DynamoDB, Apache Cassandra, Apache HBase, Redis
Apache Cassandra, Apache CouchDB
Four alternativesAmazon DynamoDB, MongoDB, MongoDB Atlas M0, ScyllaDB Cloud free trial
no first choiceagainst: Aiven for InfluxDB, Aiven for M3DB, Amazon DocumentDB, Amazon DynamoDB, Apache Cassandra, Apache CouchDB, Azure Cosmos DB, DensoDB, Firebase Realtime Database, GCP Cloud Firestore, Google Cloud Firestore, MongoDB, Neo4j, Oracle NoSQL Database, Redis, Riak KV, Voldemort
Bold 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.
PromptModelVersion stringTime (UTC)SearchedSourcesLatency
Direct recommendationClaude Haiku 4.5claude-haiku-4-5-202510012026-11-01 14:00no06 s
Direct recommendationGPT-5.4 minigpt-5.4-mini-2026-03-172026-11-01 14:26yes46 s
Direct recommendationGemini 3.5 Flashgemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version)2026-11-01 08:43no017 s
Direct recommendationPerplexity Sonarsonar2026-11-01 09:41yes104 s
Direct recommendationGrok 4.20spacexai/grok-4.20-non-reasoning via xai2026-11-01 17:53yes511 s
Direct recommendationMistral Smallmistral/mistral-small via mistral2026-11-01 08:56yes53 s
Direct recommendationDeepSeek V4 Flashdeepseek/deepseek-v4-flash via deepinfra2026-11-01 16:42yes2231 s
Direct recommendationLlama 4 Maverickmeta/llama-4-maverick via bedrock2026-11-01 13:52yes52 s
Direct recommendationQwen 3.7 Flashalibaba/qwen3.7-flash via alibaba2026-11-01 17:27no025 s
Direct recommendationKimi K2moonshotai/kimi-k2 via novita2026-11-01 17:50yes1027 s
Direct recommendationGLM 4.7 FlashXzai/glm-4.7-flashx via zai2026-11-01 12:02yes2432 s
Direct recommendationMiniMax M2.5minimax/minimax-m2.5 via minimax2026-11-01 14:46yes522 s
Direct recommendationGPT-6 Lunagpt-6-luna2026-11-01 10:30yes37 s
Direct recommendationMuse Glimmer 30Bmeta/muse-glimmer-30b via togetherai2026-11-01 17:19yes1422 s
ParaphraseClaude Haiku 4.5claude-haiku-4-5-202510012026-11-01 11:26no05 s
ParaphraseGPT-5.4 minigpt-5.4-mini-2026-03-172026-11-01 13:42yes45 s
ParaphraseGemini 3.5 Flashgemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version)2026-11-01 12:58no017 s
ParaphrasePerplexity Sonarsonar2026-11-01 14:13yes103 s
ParaphraseGrok 4.20spacexai/grok-4.20-non-reasoning via xai2026-11-01 17:50yes512 s
ParaphraseMistral Smallmistral/mistral-small via mistral2026-11-01 15:40yes95 s
ParaphraseDeepSeek V4 Flashdeepseek/deepseek-v4-flash via deepinfra2026-11-01 13:08yes1923 s
ParaphraseLlama 4 Maverickmeta/llama-4-maverick via bedrock2026-11-01 17:54yes53 s
ParaphraseQwen 3.7 Flashalibaba/qwen3.7-flash via alibaba2026-11-01 09:04no033 s
ParaphraseKimi K2moonshotai/kimi-k2 via novita2026-11-01 16:22yes1526 s
ParaphraseGLM 4.7 FlashXzai/glm-4.7-flashx via zai2026-11-01 10:35no013 s
ParaphraseMiniMax M2.5minimax/minimax-m2.5 via minimax2026-11-01 13:54yes526 s
ParaphraseGPT-6 Lunagpt-6-luna2026-11-01 19:18yes212 s
ParaphraseMuse Glimmer 30Bmeta/muse-glimmer-30b via togetherai2026-11-01 14:39yes1521 s
ComparativeClaude Haiku 4.5claude-haiku-4-5-202510012026-11-01 17:48no06 s
ComparativeGPT-5.4 minigpt-5.4-mini-2026-03-172026-11-01 19:24yes66 s
ComparativeGemini 3.5 Flashgemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version)2026-11-01 14:37no017 s
ComparativePerplexity Sonarsonar2026-11-01 09:49yes105 s
ComparativeGrok 4.20spacexai/grok-4.20-non-reasoning via xai2026-11-01 14:21yes538 s
ComparativeMistral Smallmistral/mistral-small via mistral2026-11-01 09:27yes57 s
ComparativeDeepSeek V4 Flashdeepseek/deepseek-v4-flash via deepinfra2026-11-01 14:25yes1527 s
ComparativeLlama 4 Maverickmeta/llama-4-maverick via bedrock2026-11-01 12:09yes54 s
ComparativeQwen 3.7 Flashalibaba/qwen3.7-flash via alibaba2026-11-01 08:57yes534 s
ComparativeKimi K2moonshotai/kimi-k2 via novita2026-11-01 10:49yes1050 s
ComparativeGLM 4.7 FlashXzai/glm-4.7-flashx via zai2026-11-01 16:17yes1564 s
ComparativeMiniMax M2.5minimax/minimax-m2.5 via minimax2026-11-01 13:19no016 s
ComparativeGPT-6 Lunagpt-6-luna2026-11-01 09:52yes718 s
ComparativeMuse Glimmer 30Bmeta/muse-glimmer-30b via togetherai2026-11-01 17:00yes1432 s
Budget constrainedClaude Haiku 4.5claude-haiku-4-5-202510012026-11-01 13:14no05 s
Budget constrainedGPT-5.4 minigpt-5.4-mini-2026-03-172026-11-01 13:25no03 s
Budget constrainedGemini 3.5 Flashgemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version)2026-11-01 09:39yes520 s
Budget constrainedPerplexity Sonarsonar2026-11-01 16:16yes103 s
Budget constrainedGrok 4.20spacexai/grok-4.20-non-reasoning via xai2026-11-01 15:50yes510 s
Budget constrainedMistral Smallmistral/mistral-small via mistral2026-11-01 17:43yes53 s
Budget constrainedDeepSeek V4 Flashdeepseek/deepseek-v4-flash via deepinfra2026-11-01 12:33yes1019 s
Budget constrainedLlama 4 Maverickmeta/llama-4-maverick via bedrock2026-11-01 17:51yes54 s
Budget constrainedQwen 3.7 Flashalibaba/qwen3.7-flash via alibaba2026-11-01 11:00yes20115 s
Budget constrainedKimi K2moonshotai/kimi-k2 via novita2026-11-01 18:10yes527 s
Budget constrainedGLM 4.7 FlashXzai/glm-4.7-flashx via zai2026-11-01 11:09yes1938 s
Budget constrainedMiniMax M2.5minimax/minimax-m2.5 via minimax2026-11-01 09:19no048 s
Budget constrainedGPT-6 Lunagpt-6-luna2026-11-01 17:33yes27 s
Budget constrainedMuse Glimmer 30Bmeta/muse-glimmer-30b via togetherai2026-11-01 09:12yes1518 s
Scale constrainedClaude Haiku 4.5claude-haiku-4-5-202510012026-11-01 16:04no06 s
Scale constrainedGPT-5.4 minigpt-5.4-mini-2026-03-172026-11-01 15:12no05 s
Scale constrainedGemini 3.5 Flashgemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version)2026-11-01 10:37no017 s
Scale constrainedPerplexity Sonarsonar2026-11-01 10:44yes106 s
Scale constrainedGrok 4.20spacexai/grok-4.20-non-reasoning via xai2026-11-01 14:17yes1015 s
Scale constrainedMistral Smallmistral/mistral-small via mistral2026-11-01 15:22no09 s
Scale constrainedDeepSeek V4 Flashdeepseek/deepseek-v4-flash via deepinfra2026-11-01 18:52yes1951 s
Scale constrainedLlama 4 Maverickmeta/llama-4-maverick via bedrock2026-11-01 14:32yes53 s
Scale constrainedQwen 3.7 Flashalibaba/qwen3.7-flash via alibaba2026-11-01 16:55no032 s
Scale constrainedKimi K2moonshotai/kimi-k2 via novita2026-11-01 12:26no058 s
Scale constrainedGLM 4.7 FlashXzai/glm-4.7-flashx via zai2026-11-01 17:47yes23147 s
Scale constrainedMiniMax M2.5minimax/minimax-m2.5 via minimax2026-11-01 10:47no042 s
Scale constrainedGPT-6 Lunagpt-6-luna2026-11-01 15:24yes312 s
Scale constrainedMuse Glimmer 30Bmeta/muse-glimmer-30b via togetherai2026-11-01 10:50no04 s
Negative framingClaude Haiku 4.5claude-haiku-4-5-202510012026-11-01 19:22yes911 s
Negative framingGPT-5.4 minigpt-5.4-mini-2026-03-172026-11-01 11:50yes46 s
Negative framingGemini 3.5 Flashgemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version)2026-11-01 18:50no020 s
Negative framingPerplexity Sonarsonar2026-11-01 15:36yes105 s
Negative framingGrok 4.20spacexai/grok-4.20-non-reasoning via xai2026-11-01 14:05yes1318 s
Negative framingMistral Smallmistral/mistral-small via mistral2026-11-01 17:23yes55 s
Negative framingDeepSeek V4 Flashdeepseek/deepseek-v4-flash via deepinfra2026-11-01 19:37yes2534 s
Negative framingLlama 4 Maverickmeta/llama-4-maverick via bedrock2026-11-01 19:37yes53 s
Negative framingQwen 3.7 Flashalibaba/qwen3.7-flash via alibaba2026-11-01 16:24no035 s
Negative framingKimi K2moonshotai/kimi-k2 via novita2026-11-01 15:07yes2489 s
Negative framingGLM 4.7 FlashXzai/glm-4.7-flashx via zai2026-11-01 15:23yes2424 s
Negative framingMiniMax M2.5minimax/minimax-m2.5 via minimax2026-11-01 18:08no017 s
Negative framingGPT-6 Lunagpt-6-luna2026-11-01 11:35yes515 s
Negative framingMuse Glimmer 30Bmeta/muse-glimmer-30b via togetherai2026-11-01 16:43yes2436 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
DataStax Astra read as DataStax Astra DB
Datastax Astra read as DataStax Astra DB
MongoDB Atlas read as MongoDB
Oracle NoSQL read as Oracle NoSQL Database
Riak read as Riak KV
Unresolved, counted raw
3store / 4store
AWS Astra
AWS ElastiCache for Redis/Valkey
AWS Neptune
ActorDB
AgateDB
Aiven for InfluxDB
Aiven for M3DB
Amazon SimpleDB
AnuDB
Apache AGE
AverageDB
CurioDB
DensoDB
GCP Cloud Firestore
IBM DataStax
Isar
KuzuDB
Managed Redis / Valkey
Memcache
MongoDB Atlas M0
Neo4j Community Edition
PNUTS
Project Voldemort
ScyllaDB Cloud free trial
TigerGraph
Discontinued, still offered
No shut-down product was recommended here.

Also in data platform

The other categories of this function, with the leader in each.
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