# MongoDB AI visibility in Databases & Data Infrastructure

Canonical: https://devtune.ai/verticals/databases-data-infrastructure/mongodb

[Website](https://www.mongodb.com/)

Updated: 2026-10-18T18:51:18.525881+00:00
Prompts: 25
Runs: 6


## Platforms

- perplexity
- google-ai-mode
- bing-copilot-search
- chatgpt-search
- google-ai
- xai-search

Rank: 5
Total brands: 15
Measured responses: 150
Presence percent: 6
Share of voice percent: 9.239130434782608
Average position: 4.0588235294117645
Docs presence percent: 4.666666666666667
Blog presence percent: 0
Brand mention percent: 23.333333333333332


## Profile

Overview: MongoDB is a publicly traded American software company (NASDAQ: MDB) founded in 2007 and headquartered in New York City. It develops and maintains the MongoDB document database engine and its flagship cloud-managed offering, MongoDB Atlas—a multi-cloud developer data platform available on AWS, Azure, and Google Cloud. MongoDB stores data in flexible, JSON-like BSON documents rather than rigid relational tables, enabling schema-less, horizontally scalable application development. Atlas has expanded beyond its database roots to include vector search, full-text search, stream processing, analytics, and AI-ready capabilities, and now represents approximately 73% of total company revenue. As of fiscal year 2026 (ending January 31, 2026), MongoDB reported $2.46 billion in annual revenue and served more than 65,200 customers globally, including 70% of the Fortune 100.
Product summary: MongoDB Atlas is a fully managed, multi-cloud developer data platform that unifies operational, vector, search, time-series, and streaming data workloads within a single developer experience. The core MongoDB database engine uses a flexible document model (BSON/JSON) enabling agile schema design and horizontal scalability through automatic sharding. Atlas layers managed infrastructure automation, integrated Atlas Vector Search for AI and RAG applications, Atlas Search (Lucene-based full-text), Atlas Stream Processing (Kafka-native), Queryable Encryption, Atlas Charts, and a rich integration ecosystem on top of the database engine. Self-managed options (Community Edition and Enterprise Advanced) are available for on-premises or private cloud deployments.


### Key capabilities

- Flexible document data model (BSON/JSON) with dynamic schema and no rigid table structure
- MongoDB Atlas fully managed multi-cloud database on AWS, Azure, and Google Cloud
- Atlas Vector Search for semantic search, RAG, and generative AI applications
- Atlas Full-Text Search with integrated Lucene-based search engine
- Atlas Stream Processing with native Apache Kafka integration
- Multi-document ACID transactions and rich secondary indexing
- Horizontal scaling via automatic sharding and replica sets
- Queryable Encryption enabling queries directly on encrypted data
- Atlas Data Federation for unified querying across Atlas and cloud object storage
- Relational Migrator for schema conversion and migration from relational databases



### Target users

- Application developers and engineering teams building cloud-native or AI-powered applications
- Platform and infrastructure engineers managing large-scale, distributed data architectures
- Enterprise architects and DBAs modernizing legacy relational database estates
- Data scientists and ML engineers building RAG pipelines and vector search applications
- DevOps and SRE teams requiring fully managed, auto-scaling cloud databases
- Startups and ISVs building mobile, gaming, or SaaS products on flexible data models



### Key use cases

- AI-native and generative AI application development (RAG pipelines, semantic search)
- Modern web, mobile, and microservices application backends
- Legacy relational database modernization and migration
- Real-time operational analytics and application-driven reporting
- Content management, product catalogs, and e-commerce backends
- IoT and connected device data ingestion and management
- Gaming backends requiring flexible, high-throughput data storage
- Financial services transaction processing and fraud detection

Integrations ecosystem: MongoDB Atlas integrates with 100+ third-party services and tools. Cloud providers: AWS, Microsoft Azure, and Google Cloud (multi-cloud deployment). Data and AI ecosystem: Confluent (Kafka), Databricks, LangChain, Cohere, Fireworks AI, Anthropic, and Hugging Face. BI and observability: Datadog, Atlas SQL Interface (for Tableau and other SQL-based BI tools), and Atlas Charts. Systems integrators in the MongoDB AI Applications Program (MAAP) include Accenture, Capgemini, TCS, Tech Mahindra, IBM, and QuantumBlack (McKinsey). Native tooling includes MongoDB Compass (GUI), Relational Migrator, Atlas Stream Processing (Kafka-native), Kubernetes Operator, and Ops Manager for self-managed deployments.
Pricing summary: MongoDB Atlas offers three tiers: Free (M0, $0/month, 512 MB storage, shared compute, free forever), Flex ($0.011/hr, up to ~$30/month, 5 GB storage, usage-based burst), and Dedicated starting at $0.08/hr (~$56.94/month for M10 with 10 GB storage and 2 GB RAM), scaling to M700 ($33.26/hr, 768 GB RAM, 96 vCPUs). Add-on services include Atlas Search Nodes ($0.12–$3.27/hr), Atlas Vector Search Nodes (same tier pricing), Atlas Stream Processing ($0.06–$2.49/hr per processor), Data Federation ($5/TB processed), and Online Archive (from $0.001578/GB/month). Enterprise Advanced (self-managed, on-premises) is sold via custom contract with consultative support. All Atlas tiers are billed hourly on a pay-as-you-go basis. Startup, educator, and student credits are available.
Review summary: MongoDB earns strong reviews across major analyst platforms, rated 4.5/5 from over 1,200 verified Gartner Peer Insights reviews in the Cloud Database Management Systems category. Users consistently praise its flexible document schema, ease of initial setup, horizontal scalability, and broad multi-language driver support. The Atlas vector search capability has received notable positive attention from AI engineers. Common criticisms include the complexity of multi-document joins compared to SQL, unexpected Atlas cost increases at scale, a steeper learning curve for advanced aggregation pipelines, and challenges with VPC and network connectivity configuration in Atlas.
Competitive positioning: MongoDB positions itself as the world's leading modern developer data platform and the only pure-play database provider named a Leader in the Gartner Magic Quadrant for Cloud Database Management Systems for three consecutive years (2023–2025). Its core differentiator is a flexible BSON/JSON document model combined with a fully managed, AI-ready cloud platform (Atlas) that unifies operational data, vector search, full-text search, stream processing, and analytics in a single developer experience. Primary competition comes from relational databases (PostgreSQL, MySQL) and cloud-native hyperscaler offerings (AWS DocumentDB, Azure Cosmos DB). Within this vertical, MongoDB faces Redis for real-time caching, CockroachDB and SingleStore for distributed SQL/HTAP, PlanetScale for MySQL-compatible cloud DB, and Supabase for Postgres-based developer platforms. MongoDB's scale (~65,200 customers, $2.46B FY2026 revenue, 70% of Fortune 100 as customers) and integrated AI positioning give it a structural advantage over most same-vertical peers.
Limitations: MongoDB's document model lacks native relational join semantics, making highly normalized or join-intensive workloads more complex than in SQL databases—requiring aggregation pipeline workarounds. Data redundancy can increase storage costs due to denormalization patterns inherent in the document model. Multi-document ACID transactions are supported but carry a notable performance overhead compared to purpose-built relational systems. High RAM consumption for active datasets can be costly at scale. The aggregation framework, while capable, is considered less expressive than SQL for complex ad-hoc analytics. Atlas consumption-based pricing can escalate unexpectedly with traffic spikes. The Server Side Public License (SSPL), introduced in 2018, is not OSI-approved, which may restrict use in certain open-source and public cloud redistribution scenarios.


### Source urls

- https://www.mongodb.com/
- https://www.mongodb.com/pricing
- https://www.mongodb.com/company
- https://investors.mongodb.com/news-releases/news-release-details/mongodb-inc-announces-fourth-quarter-and-full-year-fiscal-2025
- https://www.gartner.com/reviews/market/cloud-database-management-systems/compare/mongodb-vs-snowflake
- https://www.gartner.com/reviews/market/cloud-database-management-systems/vendor/mongodb
- https://en.wikipedia.org/wiki/MongoDB_Inc
- https://www.mongodb.com/company/blog/news/mongodb-named-leader-2024-gartner-magic-quadrant-cloud-database-management-system
- https://www.g2.com/products/mongodb/reviews
- https://www.saastr.com/mongodb-the-great-ai-turnaround-story-of-2025/
- https://tracxn.com/d/companies/mongodb/__oCW7Du3Hf9gfF2mF7uE8NDBwkojwRQYEcX3ckAmjfJs
- https://investors.mongodb.com/news-releases/news-release-details/mongodb-inc-announces-third-quarter-fiscal-2025-financial

Reviewed at: 2026-04-28T23:23:56.394+00:00


### Customer outcomes

| Customer | Summary | Metric |
| --- | --- | --- |
| Victoria's Secret | Migrated 200 databases to MongoDB Atlas in 4 months and achieved significant API performance improvement after moving away from the CouchDB ecosystem, gaining automated deployments, scalability monitoring, and vector search. | 240% improvement in API performance |
| Toyota Connected | Uses MongoDB as the core database platform for all connected vehicle services, achieving high reliability and scalability across its fleet of serviced vehicles. | 99.99% availability across 9M+ vehicles serviced |
| LG U+ | Migrated operational data from PostgreSQL to MongoDB, eliminating redundant processes, streamlining data queries, and improving resource efficiency for 3.5 million customer service calls per month. | 30% improvement in resource efficiency |
| Novo Nordisk | Reduced the time required to generate Clinical Study Reports using MongoDB, dramatically accelerating drug time-to-market with a fraction of the prior team size. | Reports generated in 10 minutes vs. 12 weeks previously |
| Coinbase | Automated cluster scaling and deployment on MongoDB Atlas, freeing engineering capacity to focus on developer and end-user product value rather than infrastructure management. | 3.25x faster cluster deployments; 60% reduction in scaling time |
| Lombard Odier | Partnered with MongoDB to migrate and modernize legacy banking technology systems using generative AI, achieving dramatically accelerated code and application migration. | Code migration 50–60x faster; application migration 20x faster than prior migrations |



### Reviews breakdown

| Platform | Score | Score max | Review count | Url |
| --- | --- | --- | --- | --- |
| Gartner Peer Insights | 4.5 | 5 | 1214 | https://www.gartner.com/reviews/market/cloud-database-management-systems/vendor/mongodb |



### Review themes



#### Praised

- Flexible document schema with no rigid table structure
- Fast and easy initial setup and cluster provisioning
- Horizontal scalability via sharding
- Rich multi-language driver and framework support
- Atlas Vector Search capability for AI and RAG applications
- Comprehensive documentation and MongoDB University resources
- Intuitive Compass GUI for schema exploration and querying
- Fully managed Atlas platform with auto-scaling and monitoring



#### Criticized

- Complex multi-document joins compared to SQL databases
- Unexpected Atlas cost spikes with usage-based scaling
- Steep learning curve for advanced aggregation pipelines
- VPC and network connectivity configuration challenges in Atlas
- Data redundancy and storage overhead from denormalization
- High RAM consumption for large active datasets
- SSPL license not OSI-approved, limiting open-source redistribution
- Less suitable for highly relational or transaction-intensive workloads




### Company facts

Founded year: 2007
Hq: New York, NY, USA


#### Founders

- Dwight Merriman
- Eliot Horowitz
- Kevin Ryan

Employees range: 5000-8000
Total funding: $311M (pre-IPO VC)
Valuation: Not available
Arr: ~$2.46B
Customer count: 65,200+
Status: Public (NASDAQ: MDB)


Readiness: Not available


## Ranking

| Display name | Pair count | Total pairs | Presence percent | Avg position |
| --- | --- | --- | --- | --- |
| Neon | 13 | 150 | 8.666666666666668 | 5.310344827586207 |
| Supabase | 13 | 150 | 8.666666666666668 | 9.76923076923077 |
| PlanetScale | 12 | 150 | 8 | 6.851851851851852 |
| CockroachDB | 12 | 150 | 8 | 7.421052631578948 |
| MongoDB | 9 | 150 | 6 | 4.0588235294117645 |
| PingCAP | 9 | 150 | 6 | 6.3076923076923075 |
| QuestDB | 6 | 150 | 4 | 7.833333333333333 |
| ClickHouse | 5 | 150 | 3.3333333333333335 | 5.9 |
| Redis | 2 | 150 | 1.3333333333333335 | 2 |
| SingleStore | 2 | 150 | 1.3333333333333335 | 4 |
| Timescale | 2 | 150 | 1.3333333333333335 | 5 |
| Turso | 2 | 150 | 1.3333333333333335 | 5 |
| Xata | 1 | 150 | 0.6666666666666667 | 4 |
| Fauna | 0 | 150 | 0 | Not available |
| Gel | 0 | 150 | 0 | Not available |



## Platform breakdown

| Platform | Prompt count | Presence rate |
| --- | --- | --- |
| perplexity | 3 | 12 |
| google-ai-mode | 2 | 8 |
| bing-copilot-search | 0 | 0 |
| chatgpt-search | 4 | 16 |
| google-ai | 0 | 0 |
| xai-search | 0 | 0 |



## Strengths

| Prompt text | Platform count | Avg position |
| --- | --- | --- |
| Which document databases handle schema evolution most smoothly — without requiring migration scripts for every change? | 3 | 1 |
| Which managed database platforms make multi-cloud portability practical — so moving between cloud providers isn't a nightmare? | 2 | 2 |



## Gaps

| Prompt text | Competitor presence count |
| --- | --- |
| Which time-series databases maintain query performance best at 10 million events per second ingestion over long retention periods? | 3 |
| Which columnar databases handle mixed OLAP and OLTP workloads well — when does it make sense to use one over a standard row-store? | 3 |
| Which developer-focused database platforms handle schema migrations with CI/CD pipeline tooling out of the box? | 3 |
| Which database platforms support branching so I can get a fresh isolated database copy per pull request for feature development? | 3 |
| What's the fastest serverless relational database to spin up and connect to a Node.js backend for a new SaaS app? | 2 |



## Topic scores

| Topic name | Prompt count | Cited prompt count |
| --- | --- | --- |
| Capability | 5 | 0 |
| Developer Experience | 5 | 2 |
| Integrations & Ecosystem | 5 | 2 |
| Performance & Reliability | 5 | 0 |
| Setup & First Run | 5 | 0 |



## Prompt results

- Prompt text: What are the best dedicated vector databases, and how do they compare to adding vector search extensions to an existing relational database?


#### Brand position by platform

Perplexity: Not available
Google-ai-mode: Not available
Bing-copilot-search: Not available
Chatgpt-search: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Perplexity

| Display name | Position |
| --- | --- |
| PlanetScale | 4 |



##### Google-ai-mode





##### Bing-copilot-search





##### Chatgpt-search





##### Google-ai





##### Xai-search




- Prompt text: What tools sync data from a primary operational database to an analytics warehouse for real-time reporting without heavy ETL infrastructure?


#### Brand position by platform

Perplexity: Not available
Google-ai-mode: Not available
Bing-copilot-search: Not available
Chatgpt-search: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Perplexity





##### Google-ai-mode





##### Bing-copilot-search





##### Chatgpt-search





##### Google-ai





##### Xai-search




- Prompt text: Which managed database platforms offer the best multi-region replication with automatic conflict resolution for write-write scenarios?


#### Brand position by platform

Perplexity: Not available
Google-ai-mode: Not available
Bing-copilot-search: Not available
Chatgpt-search: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Perplexity





##### Google-ai-mode





##### Bing-copilot-search





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| CockroachDB | 19 |



##### Google-ai





##### Xai-search




- Prompt text: Which developer-focused database platforms integrate best with IaC tools so database provisioning and config can be version-controlled?


#### Brand position by platform

Perplexity: 1
Google-ai-mode: 5
Bing-copilot-search: Not available
Chatgpt-search: 1
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Perplexity

| Display name | Position |
| --- | --- |
| MongoDB | 1 |
| CockroachDB | 3 |
| Neon | 4 |
| PlanetScale | 6 |



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Supabase | 1 |
| MongoDB | 5 |
| PlanetScale | 8 |



##### Bing-copilot-search





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| MongoDB | 1 |
| Neon | 3 |
| CockroachDB | 6 |
| PlanetScale | 8 |



##### Google-ai





##### Xai-search




- Prompt text: What tools and benchmarks help compare database platforms for high-concurrency transactional workloads before committing to one?


#### Brand position by platform

Perplexity: Not available
Google-ai-mode: Not available
Bing-copilot-search: Not available
Chatgpt-search: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Perplexity





##### Google-ai-mode





##### Bing-copilot-search





##### Chatgpt-search





##### Google-ai





##### Xai-search




- Prompt text: Which cloud database platforms support change data capture for streaming row-level changes to a message queue or event bus with low latency?


#### Brand position by platform

Perplexity: Not available
Google-ai-mode: Not available
Bing-copilot-search: Not available
Chatgpt-search: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Perplexity





##### Google-ai-mode





##### Bing-copilot-search





##### Chatgpt-search





##### Google-ai





##### Xai-search




- Prompt text: Which developer-focused databases offer the best local development experience that actually mirrors the production setup?


#### Brand position by platform

Perplexity: Not available
Google-ai-mode: Not available
Bing-copilot-search: Not available
Chatgpt-search: 33
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Perplexity

| Display name | Position |
| --- | --- |
| Neon | 1 |
| Supabase | 3 |



##### Google-ai-mode





##### Bing-copilot-search





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Neon | 10 |
| Supabase | 13 |
| MongoDB | 33 |



##### Google-ai





##### Xai-search




- Prompt text: What's the fastest serverless relational database to spin up and connect to a Node.js backend for a new SaaS app?


#### Brand position by platform

Perplexity: Not available
Google-ai-mode: Not available
Bing-copilot-search: Not available
Chatgpt-search: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Perplexity

| Display name | Position |
| --- | --- |
| Neon | 1 |
| Turso | 3 |
| Supabase | 5 |



##### Google-ai-mode





##### Bing-copilot-search





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Neon | 1 |
| Supabase | 4 |
| Turso | 6 |



##### Google-ai





##### Xai-search




- Prompt text: Which time-series databases maintain query performance best at 10 million events per second ingestion over long retention periods?


#### Brand position by platform

Perplexity: Not available
Google-ai-mode: Not available
Bing-copilot-search: Not available
Chatgpt-search: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Perplexity

| Display name | Position |
| --- | --- |
| Timescale | 4 |



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| ClickHouse | 1 |
| QuestDB | 2 |



##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| QuestDB | 2 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| ClickHouse | 1 |
| QuestDB | 6 |



##### Google-ai





##### Xai-search




- Prompt text: Which globally distributed SQL databases are worth evaluating for a latency-sensitive SaaS product compared to a traditional single-region setup?


#### Brand position by platform

Perplexity: Not available
Google-ai-mode: Not available
Bing-copilot-search: Not available
Chatgpt-search: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Perplexity

| Display name | Position |
| --- | --- |
| PlanetScale | 7 |



##### Google-ai-mode





##### Bing-copilot-search





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| CockroachDB | 9 |
| PingCAP | 15 |



##### Google-ai





##### Xai-search




- Prompt text: Which managed database services offer the best backup and point-in-time recovery for production applications handling financial transactions?


#### Brand position by platform

Perplexity: Not available
Google-ai-mode: Not available
Bing-copilot-search: Not available
Chatgpt-search: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Perplexity





##### Google-ai-mode





##### Bing-copilot-search





##### Chatgpt-search





##### Google-ai





##### Xai-search




- Prompt text: Which columnar databases handle mixed OLAP and OLTP workloads well — when does it make sense to use one over a standard row-store?


#### Brand position by platform

Perplexity: Not available
Google-ai-mode: Not available
Bing-copilot-search: Not available
Chatgpt-search: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Perplexity

| Display name | Position |
| --- | --- |
| PingCAP | 1 |
| SingleStore | 3 |
| ClickHouse | 6 |



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| PingCAP | 2 |



##### Bing-copilot-search





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| SingleStore | 1 |
| PingCAP | 2 |
| ClickHouse | 8 |



##### Google-ai





##### Xai-search




- Prompt text: Which managed database platforms have the best ORM and query builder compatibility for JavaScript and Python ecosystems?


#### Brand position by platform

Perplexity: Not available
Google-ai-mode: Not available
Bing-copilot-search: Not available
Chatgpt-search: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Perplexity

| Display name | Position |
| --- | --- |
| Neon | 1 |
| Supabase | 5 |



##### Google-ai-mode





##### Bing-copilot-search





##### Chatgpt-search





##### Google-ai





##### Xai-search




- Prompt text: Which ORMs and query builders offer the best TypeScript experience for a distributed SQL database?


#### Brand position by platform

Perplexity: Not available
Google-ai-mode: Not available
Bing-copilot-search: Not available
Chatgpt-search: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Perplexity

| Display name | Position |
| --- | --- |
| CockroachDB | 5 |



##### Google-ai-mode





##### Bing-copilot-search





##### Chatgpt-search





##### Google-ai





##### Xai-search




- Prompt text: Which managed database platforms make multi-cloud portability practical — so moving between cloud providers isn't a nightmare?


#### Brand position by platform

Perplexity: 1
Google-ai-mode: Not available
Bing-copilot-search: Not available
Chatgpt-search: 3
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Perplexity

| Display name | Position |
| --- | --- |
| MongoDB | 1 |
| CockroachDB | 4 |



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| CockroachDB | 3 |



##### Bing-copilot-search





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| CockroachDB | 1 |
| MongoDB | 3 |



##### Google-ai





##### Xai-search




- Prompt text: Which document databases handle schema evolution most smoothly — without requiring migration scripts for every change?


#### Brand position by platform

Perplexity: 1
Google-ai-mode: 1
Bing-copilot-search: Not available
Chatgpt-search: 1
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Perplexity

| Display name | Position |
| --- | --- |
| MongoDB | 1 |



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| MongoDB | 1 |



##### Bing-copilot-search





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| MongoDB | 1 |



##### Google-ai





##### Xai-search




- Prompt text: I'm evaluating managed cloud databases versus self-hosted options for a seed-stage product — what should I look at?


#### Brand position by platform

Perplexity: Not available
Google-ai-mode: Not available
Bing-copilot-search: Not available
Chatgpt-search: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Perplexity





##### Google-ai-mode





##### Bing-copilot-search





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Supabase | 5 |



##### Google-ai





##### Xai-search




- Prompt text: Which serverless database platforms maintain the best read/write throughput under sustained load with reliable autoscaling?


#### Brand position by platform

Perplexity: Not available
Google-ai-mode: Not available
Bing-copilot-search: Not available
Chatgpt-search: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Perplexity

| Display name | Position |
| --- | --- |
| ClickHouse | 6 |



##### Google-ai-mode





##### Bing-copilot-search





##### Chatgpt-search





##### Google-ai





##### Xai-search




- Prompt text: Which time-series databases have the best query authoring and debugging experience for teams coming from relational databases?


#### Brand position by platform

Perplexity: Not available
Google-ai-mode: Not available
Bing-copilot-search: Not available
Chatgpt-search: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Perplexity

| Display name | Position |
| --- | --- |
| QuestDB | 1 |



##### Google-ai-mode





##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| QuestDB | 5 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Timescale | 6 |
| QuestDB | 15 |



##### Google-ai





##### Xai-search




- Prompt text: Which cloud-native database platforms handle connection pooling best for serverless workloads with unpredictable connection spikes?


#### Brand position by platform

Perplexity: Not available
Google-ai-mode: Not available
Bing-copilot-search: Not available
Chatgpt-search: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Perplexity

| Display name | Position |
| --- | --- |
| Neon | 1 |
| Supabase | 8 |



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Neon | 2 |
| PlanetScale | 5 |



##### Bing-copilot-search





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Supabase | 6 |



##### Google-ai





##### Xai-search




- Prompt text: Which developer-focused database platforms handle schema migrations with CI/CD pipeline tooling out of the box?


#### Brand position by platform

Perplexity: Not available
Google-ai-mode: Not available
Bing-copilot-search: Not available
Chatgpt-search: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Perplexity

| Display name | Position |
| --- | --- |
| PlanetScale | 1 |
| Neon | 4 |



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Supabase | 2 |
| PlanetScale | 4 |



##### Bing-copilot-search





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Supabase | 2 |
| Neon | 11 |
| PlanetScale | 13 |



##### Google-ai





##### Xai-search




- Prompt text: What in-memory caching tools integrate best with persistent databases — and which are worth adding versus just optimizing primary database queries?


#### Brand position by platform

Perplexity: Not available
Google-ai-mode: Not available
Bing-copilot-search: Not available
Chatgpt-search: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Perplexity

| Display name | Position |
| --- | --- |
| Redis | 1 |



##### Google-ai-mode





##### Bing-copilot-search





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Redis | 2 |



##### Google-ai





##### Xai-search




- Prompt text: Which distributed SQL platforms support migrating from a legacy relational database with minimal downtime for a production application?


#### Brand position by platform

Perplexity: Not available
Google-ai-mode: Not available
Bing-copilot-search: Not available
Chatgpt-search: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Perplexity

| Display name | Position |
| --- | --- |
| CockroachDB | 1 |
| PingCAP | 5 |



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| CockroachDB | 3 |
| PingCAP | 6 |



##### Bing-copilot-search





##### Chatgpt-search





##### Google-ai





##### Xai-search




- Prompt text: Which database platforms support branching so I can get a fresh isolated database copy per pull request for feature development?


#### Brand position by platform

Perplexity: Not available
Google-ai-mode: Not available
Bing-copilot-search: Not available
Chatgpt-search: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Perplexity

| Display name | Position |
| --- | --- |
| Neon | 2 |
| PlanetScale | 3 |



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Xata | 1 |
| Supabase | 4 |
| PlanetScale | 8 |



##### Bing-copilot-search





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Neon | 1 |
| Supabase | 3 |
| PlanetScale | 6 |



##### Google-ai





##### Xai-search




- Prompt text: Which distributed SQL databases handle automatic failover most reliably when a node goes down — with the fastest recovery times?


#### Brand position by platform

Perplexity: Not available
Google-ai-mode: Not available
Bing-copilot-search: Not available
Chatgpt-search: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Perplexity

| Display name | Position |
| --- | --- |
| CockroachDB | 3 |



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| CockroachDB | 3 |
| PingCAP | 4 |



##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| PingCAP | 6 |



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| PingCAP | 9 |



##### Google-ai





##### Xai-search







## Top sources

| Url | Title | Domain | Logo url | Source vertical | Content type | Citation count | Last30d count |
| --- | --- | --- | --- | --- | --- | --- | --- |
| https://www.mongodb.com/docs/atlas/cluster-config/multi-cloud-distribution/ | Configure High Availability and Workload Isolation - Atlas | mongodb.com | Not available | commercial | article | 5 | 5 |
| https://www.mongodb.com/docs/atlas/ | Database Editions | mongodb.com | Not available | commercial | product_page | 4 | 4 |
| https://www.mongodb.com/docs/atlas/architecture/current/deployment-paradigms/multi-cloud/ | Multi-Cloud Deployment Paradigm - Atlas Architecture Center | mongodb.com | Not available | commercial | product_page | 4 | 4 |
| https://www.mongodb.com/docs/atlas/terraform/ | Get Started with Terraform and the MongoDB Atlas Provider - Atlas | mongodb.com | Not available | commercial | product_page | 4 | 4 |
| https://www.mongodb.com/products/integrations/hashicorp-terraform | HashiCorp Terraform And MongoDB Atlas | mongodb.com | Not available | commercial | product_page | 3 | 3 |
| https://www.mongodb.com/docs/atlas/reference/faq/deployment/ | FAQ: Deployment - Atlas | mongodb.com | Not available | commercial | documentation | 3 | 3 |
| https://www.mongodb.com/resources/basics/unstructured-data/schemaless | MongoDB's Flexible Schema: Unpacking The "Schemaless Database" | mongodb.com | Not available | commercial | documentation | 3 | 3 |
| https://www.mongodb.com/docs/rapid/core/schema-validation/ | Schema Validation - Database Manual | mongodb.com | Not available | commercial | documentation | 2 | 2 |



## Response excerpts

| Prompt text | Platform | Excerpt |
| --- | --- | --- |
| What are the best dedicated vector databases, and how do they compare to adding vector search extensions to an existing relational database? | bing-copilot-search | \| Inductivee](https://www.inductivee.com/blog/vector-database-performance-benchmarks-2025) ## 🗄️ Vector Search Extensions in Relational Databases Examples: pgvector(Postgres), MongoDB Atlas Vector Search, MySQL HeatWave ML. |
| What tools sync data from a primary operational database to an analytics warehouse for real-time reporting without heavy ETL infrastructure? | bing-copilot-search | CDC Replication Engines * Spice AI: Creates a continuously updated analytics replica of PostgreSQL, MySQL, or MongoDB using native CDC (WAL, binlog, oplog). |
| Which developer-focused database platforms integrate best with IaC tools so database provisioning and config can be version-controlled? | bing-copilot-search | ...sion-controlled CockroachDB\| Terraform provider\| Cloud-native SQL DB with IaC support for clusters, users, roles MongoDB Atlas\| Terraform & Pulumi providers\| Atlas-specific IaC modules for clusters, users, backups, network peering Postgr... |



## Competitor excerpts

| Platform | Competitor name | Excerpt |
| --- | --- | --- |
| google-ai-mode | ClickHouse | ...he systems proven to handle this tier of sustained ingestion while maintaining high query performance include: * * ClickHouse * How it handles 10M+ EPS & Retention: ClickHouse is an open-source, columnar OLAP database built explicitly fo... |
| google-ai-mode | QuestDB | ...etflix optimized its petabyte-scale logging system with](https://clickhouse.com/blog/netflix-petabyte-scale-logging) * QuestDB * How it handles 10M+ EPS & Retention: QuestDB is engineered from the ground up for high-throughput time-series... |
| bing-copilot-search | QuestDB | For sustained query performance at extreme ingestion rates (≈10M events/sec) with long retention, the strongest candidates are QuestDB, ClickHouse, and InfluxDB 3.0, with TimescaleDB viable when SQL compatibility is critical. |
| chatgpt-search | ClickHouse | ## 1. ClickHouse Best for analytical queries A strong first choice for large event datasets, high-cardinality dimensions, aggregations, and queries spanning weeks or years. |
| perplexity | SingleStore | \| \| SingleStore \| Offers in-memory rowstore tables for demanding point-lookup and update-heavy transactions, plus on-disk columnstore/“Universal Storage” with features such as indexes, row-level locking, and upserts for mixed workloads. |
| google-ai-mode | PingCAP | pingcap.com/article/tidb-the-ultimate-htap-database-for-modern-applications/) * * OLTP needs fast single-row lookups, heavy concurrent writes, and strict ACID guarantees (traditionally best on row-stores like PostgreSQL or MySQL). |
| chatgpt-search | SingleStore | ## 2. SingleStore Best for mixed application SQL and real-time analytics Combines rowstore and columnstore table options in a distributed SQL database. |
| chatgpt-search | PingCAP | pingcap.com/tidb/stable/tiflash-overview/)Primary Key tableData Update and Delete ## 3. When does a columnar database beat a standard row-store? |
| perplexity | PlanetScale | PlanetScale is the clearest fit if you mean schema changes managed end-to-end by the database platform: developers make changes on a branch, then use built-in deploy requests to review and apply them to production. |
| google-ai-mode | Supabase | Automated database branching with GitHub Actions - Neon Guides * Supabase * _How it works:_ Supabase features a native Supabase GitHub Integration that connects your repository directly to your Postgres project. |
| chatgpt-search | Supabase | If you want a developer-focused database platform that handles schema migrations as part of a modern CI/CD workflow, the strongest options are Supabase, Prisma, and Atlas. |
| perplexity | Neon | ...nching for isolated PR environments, but they differ in what a branch copies: \| Platform \| Database \| What a new branch starts with \| \|---\|---\|---\| \| Neon \| PostgreSQL \| A copy-on-write branch based on a point-in-time reference to the parent’s data. |



## Trend

Visibility delta: -0.0727272727272732
Avg position delta: 1.3088235294117645
Citation count delta: 9