Index › Data platform › NoSQL › Small business › September 2026 Edition

NoSQL databases for small business buyers

Asked as “NoSQL database”, and as “document or key-value database service”, on behalf of a small B2B company. 52 first choices recorded across the direct, paraphrase, budget and scale prompts, twelve models each.

Standing

MongoDB

Clear leader

77% of first choices, clear leader.

ShowinginAll 67 categories in the September 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 business

MongoDB77%Clear leaderThis page Mid-market

MongoDB59%Clear leaderStanding →Enterprise

MongoDB53%Clear leaderStanding →

01The standing

Share is the count of first choices across the direct, paraphrase, budget and scale prompts, over all twelve models, for a small B2B company. Ordered by share.

ProductFirst-choice shareNegative rateLabelsQuadrant

MongoDB9%74endorsed leader

Google Cloud Firestore4%23accepted challenger

PostgreSQL0%23accepted challenger

Amazon DynamoDB17%54accepted challenger

Redis13%45accepted challenger

Couchbase28%25criticized challenger

Show the five products at 0%, ordered by negative rate

Apache HBase90%10criticized challenger

ScyllaDB70%10criticized challenger

Apache Cassandra62%37criticized challenger

Neo4j37%19criticized challenger

Apache CouchDB23%13accepted challenger

Bars are the share of first choices, 0 to 100Every product with at least 10 labels here. Every product name links to its vendor page.

Head to head

MongoDB vs Amazon DynamoDB MongoDB vs Couchbase Amazon DynamoDB vs Couchbase

One product takes 77% of first choices here, so the chart would put ten 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. Five products carry a negative rate above 25% in this category. Jump to the standing

02What they warned about

Eight of twelve models held their first choice under the paraphrase. Claude Haiku 4.5, Mistral Small, Llama 4 Maverick and Kimi K2 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

62%

23 of 37 labels negative · 11 of 12 models · 6 hard negative

“Databases like **Apache Cassandra** and **HBase** require significant expertise.... introduce operational complexity that small teams may struggle to manage.” MiniMax M2.5, negative prompt

Apache HBase

90%

9 of 10 labels negative · 9 of 12 models · 6 hard negative

“Best avoided unless you already operate Hadoop infrastructure, which most small businesses don't.” DeepSeek V4 Flash, negative prompt

Amazon DynamoDB

17%

9 of 54 labels negative · 7 of 12 models

“should be cautious about or avoid include those that are not suitable for simple needs, such as key-value databases like Amazon DynamoDB” Llama 4 Maverick, negative prompt

Neo4j

37%

7 of 19 labels negative · 6 of 12 models · 2 hard negative

“Graph Databases (e.g., Neo4j) ... **Why to Avoid:** Query Complexity ... Cost & Resources” Qwen 3.7 Flash, negative prompt

03What they cite

Citations exist only for the models that return a source list: twelve of the twelve in this edition, and all six flagship models on the expanded tier.

Sites the answers cite

54 of 72 answers in this category came back with a source list, from 12 of 12 models: citations where the model returns them, or the search results it consulted. 5 of those lists are Google grounding redirects that name no site and are left out of the counts. 623 links across 197 sites, every framing counted. Ranked by the number of answers carrying the site or page.

sourceforge.net

vendor site · SourceForge27 answers · 30 citations · 9 models

guideflow.com

vendor site · Guideflow24 answers · 24 citations · 8 models

g2.com

21 answers · 34 citations · 9 models

aerospike.com

vendor site · Aerospike21 answers · 21 citations · 7 models

mongodb.com

vendor site · MongoDB14 answers · 19 citations · 7 models

pingcap.com

14 answers · 14 citations · 6 models

thectoclub.com

13 answers · 13 citations · 6 models

1bench.dev

11 answers · 11 citations · 7 models

worldmetrics.org

10 answers · 11 citations · 7 models

topbusinesssoftware.com

10 answers · 10 citations · 6 models

couchbase.com

vendor site · Couchbase9 answers · 20 citations · 7 models

reddit.com

9 answers · 11 citations · 5 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.

guideflow.com/blog/nosql-database-software

24 answers · 8 models

sourceforge.net/software/nosql-database/for-small-business

21 answers · 8 models

aerospike.com/blog/ten-best-nosql-cloud-databases

19 answers · 7 models

pingcap.com/article/top-10-nosql-databases-to-consider-2024

14 answers · 6 models

thectoclub.com/tools/best-nosql-database

13 answers · 6 models

g2.com/categories/nosql-databases

12 answers · 8 models

aws.amazon.com/smart-business/resources-for-smb/sql-vs-nosql

9 answers · 8 models

datavid.com/blog/best-nosql-databases

9 answers · 6 models

1bench.dev/databases/nosql

8 answers · 6 models

alex-klaus.com/reasons-not-to-nosql

8 answers · 8 models

04How 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.

ModelDirect“What is the best NoSQL database for a small B2B company?”Paraphrase“Which document or key-value database service would you recommend to a small business that sells to other businesses?”Comparative“What are the top NoSQL databases for a small team and how do they differ?”Budget-constrained“What is the best NoSQL database for a small company with a tight budget?”Scale-constrained“We are a 30 person company evaluating a NoSQL database. What should we look at?”Negative“Which NoSQL databases should a small business avoid or be cautious about?”

Claude Haiku 4.5MongoDB, PostgreSQL

One alternative

Google Cloud Firestore

against: Amazon DynamoDBGoogle Cloud Firestore, MongoDBChanged

Two alternatives

Amazon DynamoDB, Redis

Firebase Realtime Database, Google Cloud Firestore, MongoDB

One alternative

Redis

Firebase, MongoDB

One alternative

Amazon DynamoDB

against: Apache Cassandrano first choicenothing named

GPT-5.4 miniMongoDB

Two alternatives

Amazon DynamoDB, Couchbase

MongoDBHeld

Two alternatives

Amazon DynamoDB, Google Cloud Firestore

Google Cloud Firestore, MongoDB

Two alternatives

Amazon DynamoDB, Redis

against: Apache Cassandra, CouchbaseMongoDB

One alternative

PostgreSQL

against: Google Cloud Firestore, Redisno first choice

One alternative

PostgreSQL

against: Apache Cassandra, Apache HBase, Couchbase, MongoDB, Neo4j, Redis

Gemini 3.5 FlashMongoDB

Three alternatives

Amazon DynamoDB, Google Cloud Firestore / Firebase, PostgreSQL

MongoDBHeld

Two alternatives

Amazon DynamoDB, Google Cloud Firestore

MongoDB

Three alternatives

Amazon DynamoDB, Google Cloud Firestore, Redis

MongoDB

Three alternatives

Amazon DynamoDB, Google Cloud Firestore, PostgreSQL

PostgreSQL

Three alternatives

Amazon DynamoDB, Google Cloud Firestore / Firebase, MongoDB

against: Apache Cassandra, Neo4j, ScyllaDBagainst: Amazon DynamoDB, Apache Accumulo, Apache Cassandra, Apache CouchDB, Apache HBase, Google Cloud Firestore / Firebase, Neo4j, Riak KV, ScyllaDB, TigerGraph

Perplexity SonarMongoDB

Three alternatives

Amazon DynamoDB, RavenDB, Redis

MongoDBHeld

Two alternatives

Amazon DynamoDB, Google Cloud Firestore

MongoDB

Six alternatives

Amazon DynamoDB, Azure Cosmos DB, Couchbase, Neo4j, RavenDB, Redis

against: Apache CassandraGoogle Cloud Firestore, MongoDBagainst: Apache Cassandra, ScyllaDBno first choiceagainst: Apache Cassandra, Apache HBase, MongoDB, Neo4j, Redis, ScyllaDB

Grok 4.1 FastMongoDB

Four alternatives

Amazon DynamoDB, Apache Cassandra, Google Cloud Firestore, Redis

MongoDBHeld

Three alternatives

Amazon DynamoDB, Google Cloud Firestore, RavenDB

against: RedisMongoDB

Two alternatives

Amazon DynamoDB, Redis

against: Apache Cassandra, CouchbaseMongoDB

Four alternatives

Apache Cassandra, Apache CouchDB, PostgreSQL, Redis

MongoDB

Four alternatives

Amazon DynamoDB, Google Cloud Bigtable, Redis, ScyllaDB

against: Apache Cassandraagainst: Apache Cassandra, Apache HBase, Couchbase, MongoDB, Oracle NoSQL Database, Redis, Self-Hosted Elasticsearch

Mistral SmallMongoDB

Two alternatives

Firebase, restdb.io

Google Cloud Firestore, MongoDBChanged

Two alternatives

Amazon DynamoDB, Valkey

Apache CouchDB, MongoDB

Three alternatives

Apache Cassandra, RavenDB, Redis

Google Cloud Firestore, MongoDB

One alternative

RavenDB

against: Apache CassandraCouchbase, MongoDB

Three alternatives

ArangoDB, Neo4j, Redis

against: Amazon DynamoDB, Apache Cassandra, Azure Cosmos DB, ScyllaDBagainst: Apache Cassandra, Apache HBase, Neo4j

DeepSeek V4 FlashMongoDB

One alternative

PostgreSQL

against: Amazon DynamoDBMongoDBHeld

Two alternatives

Amazon DynamoDB, Google Cloud Firestore

MongoDB

Three alternatives

Amazon DynamoDB, Firebase / Cloud Firestore, Redis

against: Apache CassandraMongoDB, Redis

One alternative

Amazon DynamoDB

against: Apache CassandraMongoDB

Two alternatives

Amazon DynamoDB, Redis

against: Apache Cassandra, ScyllaDBagainst: Amazon DynamoDB, Apache Cassandra, Apache CouchDB, Apache HBase, Couchbase, MongoDB

Llama 4 Maverickno first choiceMongoDBChanged

Three alternatives

Amazon DynamoDB, Azure Cosmos DB, Redis

no first choicerestdb.io

Two alternatives

Apache Cassandra, Azure Cosmos DB

no first choiceagainst: Amazon DynamoDB, Couchbase, Oracle NoSQL Database

Qwen 3.7 FlashMongoDB

Three alternatives

Amazon DynamoDB, Google Cloud Firestore, Neo4j

MongoDBHeld

Three alternatives

Amazon DynamoDB, Firebase, Supabase

MongoDB

Two alternatives

Google Firebase / Firestore, Redis

MongoDB

Three alternatives

Amazon DynamoDB, Firebase, Redis

no first choice

Two alternatives

MongoDB, PostgreSQL

against: Apache Cassandra, RethinkDB, Riak, ScyllaDBagainst: Apache Cassandra, Apache HBase, Memcached, MongooseIM, Neo4j, WorldServer

Kimi K2RavenDB

Two alternatives

MongoDB, PostgreSQL

MongoDBChanged

One alternative

Supabase

against: Amazon DynamoDBMongoDB

Four alternatives

Couchbase, Firebase / Cloud Firestore, PostgreSQL, Redis

MongoDB

Three alternatives

Apache CouchDB, PostgreSQL, RavenDB

MongoDB

Three alternatives

Amazon DynamoDB, Couchbase, Redis

against: Amazon DynamoDB, Apache Cassandra, MongoDB

GLM 4.7 FlashXMongoDB

Four alternatives

Amazon DynamoDB, Azure Cosmos DB, Google Cloud Firestore, Redis

MongoDBHeld

Two alternatives

Amazon DynamoDB, Redis

MongoDB, Redis

Five alternatives

Amazon DynamoDB, Apache Cassandra, Couchbase, InfluxDB, Neo4j

MongoDB

Five alternatives

Apache Cassandra, Apache CouchDB, PostgreSQL, Redis, SQLite

against: MongoDBno first choiceagainst: Amazon DynamoDB, Amazon Neptune, Apache Cassandra, Apache CouchDB, Apache HBase, ArangoDB, Couchbase, MongoDB, Neo4j, Oracle NoSQL Database, Redis

MiniMax M2.5MongoDB

Two alternatives

Firebase, RavenDB

MongoDBHeld

Two alternatives

Amazon DynamoDB, Google Cloud Firestore

MongoDB

Four alternatives

Amazon DynamoDB, Apache Cassandra, Firebase / Cloud Firestore, Redis

MongoDB

Three alternatives

Amazon DynamoDB, Apache CouchDB, Redis

Amazon DynamoDB, MongoDB

Two alternatives

PostgreSQL, Redis

against: Apache Cassandra, Apache HBase

Bold is the first choiceAlternatives are counted; the count opens them.What the answer argued against

05The 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

Seventy-two 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`	2026-09-17 09:57	no	0	5 s
Direct recommendation	GPT-5.4 mini	`gpt-5.4-mini-2026-03-17`	2026-09-17 13:07	yes	5	5 s
Direct recommendation	Gemini 3.5 Flash	`gemini-3.5-flash`	2026-09-17 11:23	yes	6	21 s
Direct recommendation	Perplexity Sonar	`sonar`	2026-09-17 10:07	yes	20	5 s
Direct recommendation	Grok 4.1 Fast	`spacexai/grok-4.1-fast-non-reasoning via vertex`	2026-09-17 12:39	yes	18	10 s
Direct recommendation	Mistral Small	`mistral/mistral-small via mistral`	2026-09-17 11:06	yes	5	4 s
Direct recommendation	DeepSeek V4 Flash	`deepseek/deepseek-v4-flash via fireworks`	2026-09-17 10:18	yes	10	15 s
Direct recommendation	Llama 4 Maverick	`meta/llama-4-maverick via bedrock`	2026-09-17 11:41	yes	5	3 s
Direct recommendation	Qwen 3.7 Flash	`alibaba/qwen3.7-flash via alibaba`	2026-09-17 12:13	no	0	41 s
Direct recommendation	Kimi K2	`moonshotai/kimi-k2 via novita`	2026-09-17 11:59	yes	15	49 s
Direct recommendation	GLM 4.7 FlashX	`zai/glm-4.7-flashx via zai`	2026-09-17 12:24	yes	15	92 s
Direct recommendation	MiniMax M2.5	`minimax/minimax-m2.5 via minimax`	2026-09-17 12:41	yes	6	91 s
Paraphrase	Claude Haiku 4.5	`claude-haiku-4-5-20251001`	2026-09-17 11:47	no	0	5 s
Paraphrase	GPT-5.4 mini	`gpt-5.4-mini-2026-03-17`	2026-09-17 09:43	yes	3	5 s
Paraphrase	Gemini 3.5 Flash	`gemini-3.5-flash`	2026-09-17 13:15	yes	8	21 s
Paraphrase	Perplexity Sonar	`sonar`	2026-09-17 11:34	yes	17	5 s
Paraphrase	Grok 4.1 Fast	`spacexai/grok-4.1-fast-non-reasoning via vertex`	2026-09-17 14:09	yes	14	8 s
Paraphrase	Mistral Small	`mistral/mistral-small via mistral`	2026-09-17 13:12	yes	10	7 s
Paraphrase	DeepSeek V4 Flash	`deepseek/deepseek-v4-flash via fireworks`	2026-09-17 12:09	yes	15	18 s
Paraphrase	Llama 4 Maverick	`meta/llama-4-maverick via bedrock`	2026-09-17 11:57	yes	5	3 s
Paraphrase	Qwen 3.7 Flash	`alibaba/qwen3.7-flash via alibaba`	2026-09-17 13:45	no	0	34 s
Paraphrase	Kimi K2	`moonshotai/kimi-k2 via novita`	2026-09-17 11:28	yes	20	24 s
Paraphrase	GLM 4.7 FlashX	`zai/glm-4.7-flashx via zai`	2026-09-17 10:48	no	0	14 s
Paraphrase	MiniMax M2.5	`minimax/minimax-m2.5 via minimax`	2026-09-17 13:33	yes	5	37 s
Comparative	Claude Haiku 4.5	`claude-haiku-4-5-20251001`	2026-09-17 10:12	no	0	5 s
Comparative	GPT-5.4 mini	`gpt-5.4-mini-2026-03-17`	2026-09-17 11:24	no	0	6 s
Comparative	Gemini 3.5 Flash	`gemini-3.5-flash`	2026-09-17 12:46	yes	10	26 s
Comparative	Perplexity Sonar	`sonar`	2026-09-17 13:56	yes	20	8 s
Comparative	Grok 4.1 Fast	`spacexai/grok-4.1-fast-non-reasoning via vertex`	2026-09-17 10:01	yes	11	9 s
Comparative	Mistral Small	`mistral/mistral-small via mistral`	2026-09-17 09:38	yes	10	10 s
Comparative	DeepSeek V4 Flash	`deepseek/deepseek-v4-flash via fireworks`	2026-09-17 13:06	yes	10	17 s
Comparative	Llama 4 Maverick	`meta/llama-4-maverick via bedrock`	2026-09-17 09:52	yes	5	3 s
Comparative	Qwen 3.7 Flash	`alibaba/qwen3.7-flash via alibaba`	2026-09-17 10:19	no	0	41 s
Comparative	Kimi K2	`moonshotai/kimi-k2 via novita`	2026-09-17 09:50	yes	10	41 s
Comparative	GLM 4.7 FlashX	`zai/glm-4.7-flashx via zai`	2026-09-17 13:26	yes	10	109 s
Comparative	MiniMax M2.5	`minimax/minimax-m2.5 via minimax`	2026-09-17 12:35	yes	5	64 s
Budget constrained	Claude Haiku 4.5	`claude-haiku-4-5-20251001`	2026-09-17 13:12	no	0	4 s
Budget constrained	GPT-5.4 mini	`gpt-5.4-mini-2026-03-17`	2026-09-17 13:12	no	0	3 s
Budget constrained	Gemini 3.5 Flash	`gemini-3.5-flash`	2026-09-17 12:44	yes	7	24 s
Budget constrained	Perplexity Sonar	`sonar`	2026-09-17 12:57	yes	20	5 s
Budget constrained	Grok 4.1 Fast	`spacexai/grok-4.1-fast-non-reasoning via vertex`	2026-09-17 09:56	yes	15	8 s
Budget constrained	Mistral Small	`mistral/mistral-small via mistral`	2026-09-17 12:03	yes	5	5 s
Budget constrained	DeepSeek V4 Flash	`deepseek/deepseek-v4-flash via fireworks`	2026-09-17 10:26	yes	10	13 s
Budget constrained	Llama 4 Maverick	`meta/llama-4-maverick via bedrock`	2026-09-17 13:18	yes	5	2 s
Budget constrained	Qwen 3.7 Flash	`alibaba/qwen3.7-flash via alibaba`	2026-09-17 10:32	no	0	35 s
Budget constrained	Kimi K2	`moonshotai/kimi-k2 via novita`	2026-09-17 12:43	yes	15	46 s
Budget constrained	GLM 4.7 FlashX	`zai/glm-4.7-flashx via zai`	2026-09-17 10:44	yes	17	85 s
Budget constrained	MiniMax M2.5	`minimax/minimax-m2.5 via minimax`	2026-09-17 13:16	yes	5	52 s
Scale constrained	Claude Haiku 4.5	`claude-haiku-4-5-20251001`	2026-09-17 11:34	no	0	5 s
Scale constrained	GPT-5.4 mini	`gpt-5.4-mini-2026-03-17`	2026-09-17 11:01	no	0	9 s
Scale constrained	Gemini 3.5 Flash	`gemini-3.5-flash`	2026-09-17 14:14	no	0	15 s
Scale constrained	Perplexity Sonar	`sonar`	2026-09-17 14:10	yes	20	14 s
Scale constrained	Grok 4.1 Fast	`spacexai/grok-4.1-fast-non-reasoning via vertex`	2026-09-17 11:32	no	0	6 s
Scale constrained	Mistral Small	`mistral/mistral-small via mistral`	2026-09-17 14:01	no	0	6 s
Scale constrained	DeepSeek V4 Flash	`deepseek/deepseek-v4-flash via fireworks`	2026-09-17 10:33	yes	14	22 s
Scale constrained	Llama 4 Maverick	`meta/llama-4-maverick via bedrock`	2026-09-17 12:00	yes	5	4 s
Scale constrained	Qwen 3.7 Flash	`alibaba/qwen3.7-flash via alibaba`	2026-09-17 11:02	no	0	36 s
Scale constrained	Kimi K2	`moonshotai/kimi-k2 via novita`	2026-09-17 13:35	yes	20	33 s
Scale constrained	GLM 4.7 FlashX	`zai/glm-4.7-flashx via zai`	2026-09-17 09:35	yes	10	24 s
Scale constrained	MiniMax M2.5	`minimax/minimax-m2.5 via minimax`	2026-09-17 12:43	yes	5	38 s
Negative framing	Claude Haiku 4.5	`claude-haiku-4-5-20251001`	2026-09-17 13:12	yes	17	8 s
Negative framing	GPT-5.4 mini	`gpt-5.4-mini-2026-03-17`	2026-09-17 14:12	no	0	6 s
Negative framing	Gemini 3.5 Flash	`gemini-3.5-flash`	2026-09-17 13:18	yes	9	27 s
Negative framing	Perplexity Sonar	`sonar`	2026-09-17 09:53	yes	20	8 s
Negative framing	Grok 4.1 Fast	`spacexai/grok-4.1-fast-non-reasoning via vertex`	2026-09-17 11:12	yes	39	20 s
Negative framing	Mistral Small	`mistral/mistral-small via mistral`	2026-09-17 12:45	yes	5	7 s
Negative framing	DeepSeek V4 Flash	`deepseek/deepseek-v4-flash via fireworks`	2026-09-17 11:28	yes	30	25 s
Negative framing	Llama 4 Maverick	`meta/llama-4-maverick via bedrock`	2026-09-17 12:55	yes	5	3 s
Negative framing	Qwen 3.7 Flash	`alibaba/qwen3.7-flash via alibaba`	2026-09-17 09:41	yes	15	48 s
Negative framing	Kimi K2	`moonshotai/kimi-k2 via novita`	2026-09-17 11:54	yes	20	34 s
Negative framing	GLM 4.7 FlashX	`zai/glm-4.7-flashx via zai`	2026-09-17 13:42	yes	28	118 s
Negative framing	MiniMax M2.5	`minimax/minimax-m2.5 via minimax`	2026-09-17 09:23	yes	9	41 s

Normalization in this category

Every judgment call made between the raw labels and the numbers above, listed so it is visible and reversible.

Category-scoped readings

MongoDB Atlas read as MongoDB

Oracle NoSQL read as Oracle NoSQL Database

Unresolved, counted raw

Apache Accumulo

Convex

MongooseIM

TigerGraph

WorldServer

Discontinued, still offered

No shut-down product was recommended here.

NoSQL databases for small business buyers

By buyer segment

01The standing

02What they warned about

03What they cite

Sites the answers cite

Pages the answers cite

04How they answered

05The record

Normalization in this category

Also in data platform