# Timescale AI visibility in Databases & Data Infrastructure

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

[Website](https://www.timescale.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: 11
Total brands: 15
Measured responses: 150
Presence percent: 1.3333333333333335
Share of voice percent: 1.0869565217391304
Average position: 5
Docs presence percent: 0.6666666666666667
Blog presence percent: 0
Brand mention percent: 1.3333333333333335


## Profile

Overview: Timescale (legally Timescale, Inc., now operating as Tiger Data) is the creator of TimescaleDB, an open-source time-series database built as an extension to PostgreSQL. Founded in 2015 by Ajay Kulkarni and Michael Freedman, the company offers a fully managed cloud platform (Tiger Cloud) and a self-managed enterprise edition alongside the open-source core. TimescaleDB adds automatic partitioning, hybrid row/columnar storage, columnar compression, tiered storage, and over 200 time-series SQL functions to standard PostgreSQL—enabling petabyte-scale time-series workloads without abandoning SQL or the Postgres ecosystem. The platform serves use cases including IoT telemetry, financial tick data, IT observability, and AI/ML data pipelines, with 3M+ active databases and 2,000+ paying customers reported as of 2025.
Product summary: Timescale (Tiger Data) provides a PostgreSQL-native time-series database platform: the open-source TimescaleDB extension, the fully managed Tiger Cloud (available on AWS and Azure Marketplaces), and TimescaleDB Enterprise for on-premises and private cloud deployments. Key technical primitives include Hypertables for automatic partitioning, Hypercore for hybrid row/columnar storage, columnar compression up to 95%, tiered storage to object storage, continuous aggregates for real-time materialized views, 200+ time-series SQL hyperfunctions, vector search via pgvectorscale and pg_textsearch, and TigerLake for native Apache Iceberg lakehouse integration.


### Key capabilities

- Automatic time-based and key-based partitioning via Hypertables for fast ingest at scale
- Hybrid row/columnar storage engine (Hypercore) for combined OLTP and OLAP workloads
- Up to 95% columnar compression with filters and aggregates applied directly on compressed data
- Tiered storage: hot SSD tier plus low-cost object storage ($0.021/GB-month) with unified SQL access
- Continuous aggregates (incremental materialized views) for sub-millisecond dashboard queries
- 200+ time-series SQL hyperfunctions (time_bucket, time_bucket_gapfill, etc.)
- Native vector search via pgvectorscale (DiskANN) and BM25 full-text search via pg_textsearch
- Lakehouse integration: ingest from Kafka/S3, replicate to Apache Iceberg (TigerLake)
- Fully managed cloud (Tiger Cloud) with disaggregated compute and storage, Multi-AZ HA, PITR
- Open-source TimescaleDB as a Postgres extension; self-managed enterprise edition available



### Target users

- Backend and data engineers building time-series or IoT applications
- DevOps and SRE teams managing infrastructure metrics and observability pipelines
- Financial and crypto data engineers requiring tick data and time-weighted analytics
- Industrial and energy sector developers handling sensor telemetry at scale
- AI/ML engineers building RAG pipelines or agentic memory on Postgres
- Platform engineering teams adopting cloud-native PostgreSQL infrastructure



### Key use cases

- IoT and industrial sensor data ingestion and analytics
- Financial market data, crypto tick data, and time-weighted average calculations
- IT observability, infrastructure metrics, and application performance monitoring
- Energy, oil & gas, and utilities operational data management
- Web3 and blockchain on-chain event analytics
- SaaS product analytics and event tracking at scale
- AI/ML feature stores and agentic memory built on Postgres
- Real-time dashboards combining operational and historical data

Integrations ecosystem: Timescale integrates with 75+ verified tools on G2, spanning cloud providers (AWS Marketplace, Azure Marketplace), streaming platforms (Apache Kafka, Confluent, Redpanda, Flink), ETL/ELT tools (Airbyte, Fivetran, dbt, Estuary), observability stacks (Grafana, Prometheus, OpenTelemetry, New Relic, IBM Instana), BI/visualization tools (Tableau, Looker, Metabase, Superset, Power BI), AI/ML frameworks (LangChain, Amazon SageMaker), and infrastructure tools (Terraform, Kubernetes, Pulumi). Open-source extensions pgvectorscale and pg_textsearch plug into the broader pgvector/Postgres AI ecosystem. TigerLake provides native lakehouse integration to Apache Iceberg and Amazon S3.
Pricing summary: Tiger Cloud uses consumption-based hourly billing with no credit card required for a 30-day free trial. Performance plan: compute starts at $30/month, storage at $0.177/GB-month (based on 5x average compression). Scale plan: compute starts at $36/month, storage at $0.212/GB-month, includes unlimited tiered storage at $0.021/GB-month, multi-node HA, unlimited VPCs, SOC 2 report. Enterprise plan: custom pricing with 24/7 production SLAs, HIPAA compliance, SAML SSO, cross-region backups, and up to 64 CPU/256 GB per service. Open-source TimescaleDB is free under the Timescale License.
Review summary: On G2, Tiger Data (the rebranded Timescale Cloud product) holds a 4.6/5 rating from 33 verified reviews, with 72% 5-star ratings. Reviewers consistently praise fast ingest speeds, seamless PostgreSQL compatibility, easy setup, significant storage cost savings from compression, and strong community/documentation. Common criticisms include pricing perceived as high for small projects, UI slowness with many tables, and limited advanced vector visualization features compared to dedicated vector databases.
Competitive positioning: Timescale (now operating as Tiger Data, legally Timescale, Inc. d/b/a Tiger Data) differentiates as the only time-series database built natively on unforked PostgreSQL, offering full SQL compatibility and the entire Postgres ecosystem rather than a proprietary query language. It targets developers who want petabyte-scale time-series performance without abandoning relational familiarity. Its open-core model (open-source TimescaleDB + fully managed Tiger Cloud) addresses both self-hosted and cloud-native buyers, competing directly against specialized time-series stores (QuestDB, InfluxDB) and broad analytical databases (ClickHouse, SingleStore) while overlapping with Postgres-centric cloud platforms (Neon, Supabase) on the cloud DBaaS dimension.
Limitations: Pricing is cited as high for small projects or individual developers (minimum ~$30/month for cloud compute). The web UI can become slow when managing large numbers of tables. Advanced visualization for vector data lags behind some competing vector-database products. Some enterprise disaster recovery features (cross-region backups at lower tiers) require upgrading to the Enterprise plan. Resizing databases downward after historical data loads and compression can be operationally tedious. Self-hosted deployments may require additional troubleshooting for initial setup.


### Source urls

- https://www.tigerdata.com/pricing
- https://www.g2.com/products/tigerdata/reviews
- https://www.businesswire.com/news/home/20220222005363/en/Timescale-Valuation-Rockets-to-Over-%241B-with-%24110M-Round-Marking-the-Explosive-Rise-of-Time-Series-Data
- https://www.tigerdata.com/blog/year-of-the-tiger-110-million-to-build-the-future-of-data-for-developers-worldwide
- https://github.com/timescale
- https://www.crunchbase.com/organization/timescaledb
- https://www.gartner.com/reviews/product/timescaledb
- https://aws.amazon.com/marketplace/pp/prodview-iestawpo5ihca
- https://tracxn.com/d/companies/timescale/__CF-8Ib6VOR37FFRFk73tn8IHRktNhMW9wRmT9RDEv-g

Reviewed at: 2026-04-28T23:22:38.33+00:00


### Customer outcomes

| Customer | Summary | Metric |
| --- | --- | --- |
| Flowco | Tiger Data freed up engineering team capacity and accelerated roadmap velocity for this oil & gas software company. | 66% monthly cost savings |
| Axpo | The Swiss energy company migrated from MSSQL and was able to connect 20+ systems to TimescaleDB with stable performance, after previously crashing with only 2 systems connected. | 20+ systems connected vs. 2 previously |
| Pfiefer & Langen | The manufacturing company unified real-time and historical data, streaming from TimescaleDB into Iceberg for cross-platform analytics on S3 and Athena. | Not available |
| Speedcast | The telecommunications company replaced a fragile custom pipeline of Kafka, Flink, and custom code with TigerLake as native infrastructure for streaming data from Postgres to Iceberg. | Not available |



### Reviews breakdown

| Platform | Score | Score max | Review count | Url |
| --- | --- | --- | --- | --- |
| G2 | 4.6 | 5 | 33 | https://www.g2.com/products/tigerdata/reviews |



### Review themes



#### Praised

- Fast write and ingest performance
- Full PostgreSQL compatibility and familiarity
- Quick and easy setup
- Up to 95% columnar compression with cost savings
- Continuous aggregates for real-time dashboards
- Tiered storage reducing long-term storage costs
- Active community support on Slack and Discord
- Comprehensive and production-depth documentation



#### Criticized

- Pricing high for small projects or hobby use (~$50/month minimum cited)
- Recent pricing model changes perceived negatively
- UI becomes slow when managing many tables
- Limited advanced visualization for vector data vs. dedicated vector databases
- Some enterprise DR features (cross-region backup) restricted to higher tiers
- Tedious to size down databases after historical loads and compression




### Company facts

Founded year: 2015
Hq: New York City, USA


#### Founders

- Ajay Kulkarni
- Michael Freedman

Employees range: 150-250
Total funding: $180M
Valuation: >$1B
Arr: Not available
Customer count: 2,000+ paying; 3M+ active databases
Status: Private


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 | 1 | 4 |
| google-ai-mode | 0 | 0 |
| bing-copilot-search | 0 | 0 |
| chatgpt-search | 1 | 4 |
| google-ai | 0 | 0 |
| xai-search | 0 | 0 |



## Strengths

| Prompt text | Platform count | Avg position |
| --- | --- | --- |
| Which time-series databases have the best query authoring and debugging experience for teams coming from relational databases? | 1 | 6 |



## Gaps

| Prompt text | Competitor presence count |
| --- | --- |
| Which developer-focused database platforms integrate best with IaC tools so database provisioning and config can be version-controlled? | 3 |
| 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 managed database platforms make multi-cloud portability practical — so moving between cloud providers isn't a nightmare? | 3 |
| Which document databases handle schema evolution most smoothly — without requiring migration scripts for every change? | 3 |



## Topic scores

| Topic name | Prompt count | Cited prompt count |
| --- | --- | --- |
| Capability | 5 | 0 |
| Developer Experience | 5 | 1 |
| Integrations & Ecosystem | 5 | 0 |
| Performance & Reliability | 5 | 1 |
| 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: 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 |
| --- | --- |
| 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: Not available
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: 4
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: 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 |
| --- | --- |
| 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: 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 |
| --- | --- |
| 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: 6
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://assets.timescale.com/whitepapers/Timescale_WhitePaper_Benchmarking_Influx.pdf | Benchmarking TimescaleDB vs. InfluxDB for Time-Series ... | assets.timescale.com | Not available | commercial | comparison | 1 | 1 |
| https://docs.timescale.com/use-timescale/latest/troubleshoot-timescaledb/ | Official troubleshooting documentation | docs.timescale.com | Not available | commercial | documentation | 1 | 1 |



## Response excerpts

| Prompt text | Platform | Excerpt |
| --- | --- | --- |
| Which time-series databases have the best query authoring and debugging experience for teams coming from relational databases? | chatgpt-search | Timescale's documentation specifically recommends PostgreSQL's execution-plan tooling for investigating hypertable performance. |
| Which time-series databases have the best query authoring and debugging experience for teams coming from relational databases? | google-ai-mode | timescale.com) for documentation and tooling. * 2\. |



## Competitor excerpts

| Platform | Competitor name | Excerpt |
| --- | --- | --- |
| perplexity | MongoDB | ...database provisioning and configuration, these platforms stand out: \| Platform \| IaC fit \| Best for \| \|---\|---\|---\| \| MongoDB Atlas \| Strongest overall: an official, HashiCorp-verified Terraform provider covers a broad range of Atlas resources, i... |
| perplexity | CockroachDB | \| \| CockroachDB Cloud \| Strong: its Terraform provider can provision and manage clusters and related resources. |
| google-ai-mode | Supabase | Terraform provider \| Supabase FeaturesNeon Provider \| Pulumi Registry[Docs overview \| supabase/supabase \| Terraform \| Terraform Registry](https://regis... |
| chatgpt-search | MongoDB | My top recommendation is MongoDB Atlas for the most mature database-specific Terraform integration, Neon for developer-centric PostgreSQL workflows, and CockroachDB Cloud or PlanetScale for teams that want managed databases with programmable infrastructure. |
| chatgpt-search | Neon | My top recommendation is MongoDB Atlas for the most mature database-specific Terraform integration, Neon for developer-centric PostgreSQL workflows, and CockroachDB Cloud or PlanetScale for teams that want managed databases with programmable infrastructure. |
| 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. |



## Trend

Visibility delta: 1.6
Avg position delta: Not available
Citation count delta: 2