# Gel AI visibility in Databases & Data Infrastructure Canonical: https://devtune.ai/verticals/databases-data-infrastructure/gel [Website](https://www.edgedb.com/) Updated: 2026-09-27T22:47:31.942248+00:00 Prompts: 25 Runs: 6 ## Platforms - google-ai-mode - perplexity - google-ai - bing-copilot-search - chatgpt-search - xai-search Rank: 15 Total brands: 15 Measured responses: 150 Presence percent: 0 Share of voice percent: 0 Average position: Not available Docs presence percent: 0 Blog presence percent: 0 Brand mention percent: 0 ## Profile Overview: EdgeDB (rebranded as Gel in February 2025) was an open-source, graph-relational database built on top of PostgreSQL, developed by Gel Data Inc. (formerly EdgeDB Inc.), founded in 2019 by Yury Selivanov and Elvis Pranskevichus in San Francisco. It introduced a high-level object-type data model with 'links' replacing SQL JOINs, a composable type-safe query language called EdgeQL, a native schema migrations engine, built-in authentication, AI/vector capabilities, and a managed cloud service. Positioned as a developer-experience-first alternative to traditional SQL databases and ORMs, EdgeDB raised $19M in total funding before announcing in December 2025 that Gel Data Inc. was shutting down and the team was joining Vercel. The product remains fully open source on GitHub with ~14K stars. Product summary: EdgeDB/Gel was a graph-relational database and managed cloud platform built on PostgreSQL. It offered a high-level object-type data model (replacing tables and JOINs with object types and links), its own composable query language (EdgeQL), full SQL support, declarative schema migrations, built-in authentication, AI/vector database extensions, a TypeScript query builder with code generation, and multi-language client libraries. A managed cloud service (Gel Cloud) was available with Vercel and GitHub integrations. The commercial entity shut down in December 2025; the software remains open source. ### Key capabilities - Graph-relational data model built on PostgreSQL with object types and links (no JOINs) - EdgeQL: composable, type-safe, set-based query language with no NULL - Full SQL support alongside EdgeQL (added in later versions) - Native declarative schema migrations engine - Built-in auth extension (OAuth, email/password, magic links, passkeys, WebAuthn) - AI extension with automatic embeddings, vector store, and built-in RAG endpoint - TypeScript query builder with end-to-end code generation - Built-in graphical UI (schema browser, data editor, query IDE, performance visualization) - Multi-language client libraries with zero-config connection pooling and auto-recovery - Fully managed cloud service (Gel Cloud) on AWS with HA, encryption at rest, and branching ### Target users - Full-stack JavaScript/TypeScript developers seeking type-safe data layers - Python developers building backend services or AI applications - Startup engineering teams wanting a batteries-included Postgres platform - Developers looking to replace complex ORM setups with a composable query layer - AI application developers needing integrated vector search and RAG - Teams requiring built-in authentication without separate identity services ### Key use cases - Full-stack app development with end-to-end type safety and no ORM required - AI-powered applications using built-in vector search and RAG endpoints - Rapid prototyping with schema branching and preview deployments - Applications requiring integrated auth flows without external identity providers - Multi-language backend services sharing a single declarative schema source of truth - Developer teams migrating off complex ORM stacks to a more composable data layer - Startups seeking a batteries-included Postgres-based data platform Integrations ecosystem: Gel/EdgeDB integrated natively with Vercel (marketplace partnership, automatic preview deployments), GitHub (PR-based deployment workflows), and Netlify. AI integrations supported OpenAI, Anthropic, and Mistral for embeddings and RAG. The Drizzle ORM had a sponsored partnership with Gel for JavaScript/TypeScript usage. Client libraries were available for Python, JavaScript/TypeScript, Go, Rust, Dart, .NET, and Java. OAuth integrations supported Google, GitHub, Slack, Discord, and others. GraphQL was supported out of the box. The product was compatible with most BI solutions via SQL access. Pricing summary: Prior to shutdown, Gel Cloud offered three tiers: a Free tier at $0/month (1/4 compute unit, 1/2 GiB RAM, up to 1 GB disk, community support); a Pro tier starting at $19.50/month (1/2 compute unit, 1 GiB RAM, 10 GiB storage included at $0.50/GiB overage, 100 GiB transfer, email support); and an Enterprise tier with custom pricing (priority support, AWS deployment, custom contracts, volume discounts). All prices were in USD for the aws-us-east-2 region. As of December 2, 2025, Gel Cloud no longer accepts new registrations and will fully shut down January 31, 2026. Self-hosting the open-source software remains free. Review summary: EdgeDB has very limited formal review coverage, with only 9 reviews on G2 averaging 4.0/5. Community sentiment on Hacker News, Twitter, and developer blogs was broadly enthusiastic about EdgeQL's composability, type safety, and the elimination of ORMs, with developer bloggers describing it as transformative for their workflows. Common criticisms included a steep learning curve for EdgeQL and the graph-relational data model, difficult onboarding, confusion about how it differed from ORMs, and concerns about adoption risk for a small-team startup. The company's December 2025 shutdown announcement validated concerns about long-term viability. Competitive positioning: EdgeDB (later rebranded as Gel) positioned itself as a developer-experience-first, graph-relational database built on top of PostgreSQL—targeting the space between raw SQL databases and ORMs. It competed primarily with Postgres-native developer platforms like Supabase and Neon, and developer-first databases like PlanetScale, by offering a proprietary composable query language (EdgeQL), native schema migrations, built-in auth, and AI/vector capabilities as a single integrated stack. Its founders explicitly acknowledged it sat in an awkward category often confused with ORMs, and that its novel data model and custom query language steepened adoption. As of December 2025, Gel Data Inc. has shut down and the team has joined Vercel; the open-source codebase remains available on GitHub. Limitations: Gel/EdgeDB's own founders publicly acknowledged several key limitations upon shutdown: (1) EdgeQL, while powerful, is a non-SQL query language requiring significant learning investment and community knowledge is limited; (2) the graph-relational data model diverged from the classic relational model, creating a steep conceptual learning curve and frequent confusion with ORMs; (3) the product attempted to do too much (new data model, migration engine, IO server, CLI, client libraries, UI, compilers, auth, AI, and cloud), preventing focus on polishing any single area; (4) the commercial cloud service (Gel Cloud) shut down January 31, 2026, making it unsuitable for new production workloads; (5) the small team (~14 people at Series A) and single $19M funding round limited enterprise credibility; (6) community users noted difficult onboarding and setup experience; (7) limited third-party integrations and ecosystem compared to standard Postgres tooling. ### Source urls - https://www.geldata.com/blog/gel-joins-vercel - https://www.geldata.com/pricing - https://www.geldata.com/blog/edgedb-is-now-gel-and-postgres-is-the-future - https://techcrunch.com/2022/11/07/edgedb-raises-15m-ahead-of-the-launch-of-its-cloud-database-service/ - https://www.prnewswire.com/news-releases/edgedb-raises-15m-series-a-round-to-bring-its-modernized-relational-database-for-cutting-edge-apps-to-the-cloud-301669752.html - https://www.techtarget.com/searchdatamanagement/news/252526995/EdgeDB-raises-15M-for-open-source-graph-relational-database - https://www.g2.com/products/edgedb/reviews - https://dbdb.io/db/gel - https://www.geldata.com/blog/edgedb-cloud-free-tier-how-we-stack-up-vs-planetscale-supabase-neon - https://github.com/geldata/gel - https://tracxn.com/d/companies/edgedb/__Q5SVxMqYYYVmispDbFh7y2wtd6UXPcfHc7LArtp9D7w Reviewed at: 2026-04-28T23:22:06.214+00:00 ### Customer outcomes | Customer | Summary | Metric | | --- | --- | --- | | BeatGig | The Y Combinator-backed startup reported that EdgeDB's high-level data model and EdgeQL transformed the way they built their product, allowing faster feature development without managing how relational data connects under the hood. | Not available | | Credal.ai | Credal.ai reported that using EdgeDB accelerated product development and enhanced data safety in their enterprise AI product, with EdgeDB's impact noted on developer productivity and error minimization in a fast-paced AI sector. | Not available | ### Reviews breakdown | Platform | Score | Score max | Review count | Url | | --- | --- | --- | --- | --- | | G2 | 4 | 5 | 9 | https://www.g2.com/products/edgedb/reviews | ### Review themes #### Praised - EdgeQL composability and type safety - Elimination of ORM boilerplate - Built-in schema migrations engine - Developer experience and tooling polish - Zero-config local setup - Fast query performance vs. popular ORMs - Postgres reliability as the underlying engine - Built-in auth and AI extensions reducing third-party dependencies #### Criticized - Steep learning curve for EdgeQL and graph-relational model - Confusing positioning versus ORMs - Difficult onboarding and initial setup - Rapid API changes making community resources obsolete quickly - Small community and limited third-party ecosystem - Commercial viability and adoption risk for a small-team startup - Company/cloud service shut down (Dec 2025) ### Company facts Founded year: 2019 Hq: San Francisco, USA #### Founders - Yury Selivanov - Elvis Pranskevichus Employees range: 11-50 Total funding: $19M Valuation: Not available Arr: Not available Customer count: 20,000+ monthly active users (as of Nov Status: Shut down (Gel Data Inc. dissolved Dec 2025; team joined Ver Readiness: Not available ## Ranking | Display name | Pair count | Total pairs | Presence percent | Avg position | | --- | --- | --- | --- | --- | | Neon | 11 | 150 | 7.333333333333333 | 2.739130434782609 | | Supabase | 10 | 150 | 6.666666666666667 | 4.473684210526316 | | MongoDB | 9 | 150 | 6 | 3 | | CockroachDB | 9 | 150 | 6 | 3.4705882352941178 | | ClickHouse | 6 | 150 | 4 | 3.8181818181818183 | | PlanetScale | 5 | 150 | 3.3333333333333335 | 3.2857142857142856 | | QuestDB | 5 | 150 | 3.3333333333333335 | 3.9 | | Redis | 3 | 150 | 2 | 2.75 | | PingCAP | 3 | 150 | 2 | 3.142857142857143 | | SingleStore | 3 | 150 | 2 | 3.142857142857143 | | Timescale | 2 | 150 | 1.3333333333333335 | 1 | | Xata | 1 | 150 | 0.6666666666666667 | 5 | | Turso | 1 | 150 | 0.6666666666666667 | 7 | | Fauna | 0 | 150 | 0 | Not available | | Gel | 0 | 150 | 0 | Not available | ## Platform breakdown | Platform | Prompt count | Presence rate | | --- | --- | --- | | google-ai-mode | 0 | 0 | | perplexity | 0 | 0 | | google-ai | 0 | 0 | | bing-copilot-search | 0 | 0 | | chatgpt-search | 0 | 0 | | xai-search | 0 | 0 | ## Strengths ## Gaps | Prompt text | Competitor presence count | | --- | --- | | Which columnar databases handle mixed OLAP and OLTP workloads well — when does it make sense to use one over a standard row-store? | 4 | | Which developer-focused database platforms integrate best with IaC tools so database provisioning and config can be version-controlled? | 3 | | Which globally distributed SQL databases are worth evaluating for a latency-sensitive SaaS product compared to a traditional single-region setup? | 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 | 0 | | Integrations & Ecosystem | 5 | 0 | | Performance & Reliability | 5 | 0 | | Setup & First Run | 5 | 0 | ## Prompt results - 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 Google-ai-mode: Not available Perplexity: Not available Google-ai: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Xai-search: Not available #### Platform rows ##### Google-ai-mode ##### Perplexity ##### Google-ai ##### Bing-copilot-search ##### Chatgpt-search ##### 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 Google-ai-mode: Not available Perplexity: Not available Google-ai: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Xai-search: Not available #### Platform rows ##### Google-ai-mode | Display name | Position | | --- | --- | | Neon | 1 | | Supabase | 3 | ##### Perplexity | Display name | Position | | --- | --- | | Neon | 1 | | Supabase | 2 | ##### Google-ai ##### Bing-copilot-search ##### Chatgpt-search | Display name | Position | | --- | --- | | MongoDB | 1 | | Supabase | 2 | ##### 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 Google-ai-mode: Not available Perplexity: Not available Google-ai: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Xai-search: Not available #### Platform rows ##### Google-ai-mode ##### Perplexity ##### Google-ai ##### Bing-copilot-search ##### Chatgpt-search ##### 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 Google-ai-mode: Not available Perplexity: Not available Google-ai: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Xai-search: Not available #### Platform rows ##### Google-ai-mode ##### Perplexity | Display name | Position | | --- | --- | | Neon | 1 | | Supabase | 5 | ##### Google-ai ##### Bing-copilot-search ##### Chatgpt-search | Display name | Position | | --- | --- | | Neon | 1 | | Supabase | 2 | ##### 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 Google-ai-mode: Not available Perplexity: Not available Google-ai: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Xai-search: Not available #### Platform rows ##### Google-ai-mode ##### Perplexity | Display name | Position | | --- | --- | | CockroachDB | 1 | ##### Google-ai | Display name | Position | | --- | --- | | PingCAP | 1 | ##### Bing-copilot-search ##### Chatgpt-search | Display name | Position | | --- | --- | | CockroachDB | 2 | ##### 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 Google-ai-mode: Not available Perplexity: Not available Google-ai: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Xai-search: Not available #### Platform rows ##### Google-ai-mode ##### Perplexity ##### Google-ai ##### Bing-copilot-search ##### Chatgpt-search ##### 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 Google-ai-mode: Not available Perplexity: Not available Google-ai: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Xai-search: Not available #### Platform rows ##### Google-ai-mode ##### Perplexity | Display name | Position | | --- | --- | | SingleStore | 1 | | ClickHouse | 5 | ##### Google-ai | Display name | Position | | --- | --- | | PingCAP | 1 | | ClickHouse | 6 | ##### Bing-copilot-search | Display name | Position | | --- | --- | | ClickHouse | 2 | ##### Chatgpt-search | Display name | Position | | --- | --- | | SingleStore | 1 | | ClickHouse | 3 | ##### 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 Google-ai-mode: Not available Perplexity: Not available Google-ai: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Xai-search: Not available #### Platform rows ##### Google-ai-mode | Display name | Position | | --- | --- | | CockroachDB | 3 | ##### Perplexity | Display name | Position | | --- | --- | | Neon | 1 | | Supabase | 5 | ##### Google-ai ##### Bing-copilot-search ##### Chatgpt-search ##### Xai-search - Prompt text: Which ORMs and query builders offer the best TypeScript experience for a distributed SQL database? #### Brand position by platform Google-ai-mode: Not available Perplexity: Not available Google-ai: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Xai-search: Not available #### Platform rows ##### Google-ai-mode ##### Perplexity ##### Google-ai ##### Bing-copilot-search ##### Chatgpt-search ##### 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 Google-ai-mode: Not available Perplexity: Not available Google-ai: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Xai-search: Not available #### Platform rows ##### Google-ai-mode | Display name | Position | | --- | --- | | MongoDB | 3 | ##### Perplexity | Display name | Position | | --- | --- | | CockroachDB | 1 | | MongoDB | 3 | ##### Google-ai ##### Bing-copilot-search ##### Chatgpt-search | Display name | Position | | --- | --- | | MongoDB | 2 | ##### 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 Google-ai-mode: Not available Perplexity: Not available Google-ai: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Xai-search: Not available #### Platform rows ##### Google-ai-mode ##### Perplexity | Display name | Position | | --- | --- | | Neon | 1 | | PlanetScale | 4 | ##### Google-ai | Display name | Position | | --- | --- | | Xata | 5 | ##### Bing-copilot-search ##### Chatgpt-search | Display name | Position | | --- | --- | | Supabase | 2 | | PlanetScale | 3 | ##### 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 Google-ai-mode: Not available Perplexity: Not available Google-ai: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Xai-search: Not available #### Platform rows ##### Google-ai-mode ##### Perplexity ##### Google-ai ##### Bing-copilot-search ##### Chatgpt-search ##### Xai-search - Prompt text: Which serverless database platforms maintain the best read/write throughput under sustained load with reliable autoscaling? #### Brand position by platform Google-ai-mode: Not available Perplexity: Not available Google-ai: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Xai-search: Not available #### Platform rows ##### Google-ai-mode ##### Perplexity ##### Google-ai ##### Bing-copilot-search ##### Chatgpt-search ##### Xai-search - Prompt text: Which cloud-native database platforms handle connection pooling best for serverless workloads with unpredictable connection spikes? #### Brand position by platform Google-ai-mode: Not available Perplexity: Not available Google-ai: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Xai-search: Not available #### Platform rows ##### Google-ai-mode ##### Perplexity | Display name | Position | | --- | --- | | Neon | 1 | ##### Google-ai ##### Bing-copilot-search ##### Chatgpt-search ##### 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 Google-ai-mode: Not available Perplexity: Not available Google-ai: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Xai-search: Not available #### Platform rows ##### Google-ai-mode ##### Perplexity | Display name | Position | | --- | --- | | PlanetScale | 1 | | Neon | 3 | ##### Google-ai ##### Bing-copilot-search ##### Chatgpt-search | Display name | Position | | --- | --- | | Supabase | 1 | | PlanetScale | 2 | ##### 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 Google-ai-mode: Not available Perplexity: Not available Google-ai: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Xai-search: Not available #### Platform rows ##### Google-ai-mode ##### Perplexity | Display name | Position | | --- | --- | | Redis | 4 | ##### Google-ai ##### Bing-copilot-search ##### Chatgpt-search ##### 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 Google-ai-mode: Not available Perplexity: Not available Google-ai: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Xai-search: Not available #### Platform rows ##### Google-ai-mode ##### Perplexity | Display name | Position | | --- | --- | | CockroachDB | 5 | ##### Google-ai | Display name | Position | | --- | --- | | CockroachDB | 3 | | SingleStore | 4 | ##### Bing-copilot-search ##### Chatgpt-search | Display name | Position | | --- | --- | | CockroachDB | 1 | ##### Xai-search - Prompt text: Which developer-focused databases offer the best local development experience that actually mirrors the production setup? #### Brand position by platform Google-ai-mode: Not available Perplexity: Not available Google-ai: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Xai-search: Not available #### Platform rows ##### Google-ai-mode ##### Perplexity | Display name | Position | | --- | --- | | Neon | 1 | | Supabase | 5 | ##### Google-ai ##### Bing-copilot-search ##### Chatgpt-search | Display name | Position | | --- | --- | | Supabase | 2 | | Neon | 3 | | MongoDB | 4 | | PlanetScale | 5 | | Turso | 7 | ##### Xai-search - Prompt text: Which document databases handle schema evolution most smoothly — without requiring migration scripts for every change? #### Brand position by platform Google-ai-mode: Not available Perplexity: Not available Google-ai: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Xai-search: Not available #### Platform rows ##### Google-ai-mode ##### Perplexity | Display name | Position | | --- | --- | | MongoDB | 3 | ##### Google-ai ##### Bing-copilot-search | Display name | Position | | --- | --- | | MongoDB | 1 | ##### Chatgpt-search | Display name | Position | | --- | --- | | MongoDB | 1 | ##### 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 Google-ai-mode: Not available Perplexity: Not available Google-ai: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Xai-search: Not available #### Platform rows ##### Google-ai-mode ##### Perplexity | Display name | Position | | --- | --- | | Timescale | 1 | | QuestDB | 3 | ##### Google-ai | Display name | Position | | --- | --- | | QuestDB | 5 | ##### Bing-copilot-search ##### Chatgpt-search | Display name | Position | | --- | --- | | Timescale | 1 | | QuestDB | 2 | | ClickHouse | 3 | ##### Xai-search - 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 Google-ai-mode: Not available Perplexity: Not available Google-ai: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Xai-search: Not available #### Platform rows ##### Google-ai-mode ##### Perplexity | Display name | Position | | --- | --- | | Neon | 3 | ##### Google-ai ##### Bing-copilot-search ##### Chatgpt-search | Display name | Position | | --- | --- | | MongoDB | 5 | ##### 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 Google-ai-mode: Not available Perplexity: Not available Google-ai: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Xai-search: Not available #### Platform rows ##### Google-ai-mode ##### Perplexity ##### Google-ai ##### Bing-copilot-search ##### Chatgpt-search ##### 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 Google-ai-mode: Not available Perplexity: Not available Google-ai: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Xai-search: Not available #### Platform rows ##### Google-ai-mode ##### Perplexity | Display name | Position | | --- | --- | | QuestDB | 1 | ##### Google-ai ##### Bing-copilot-search ##### Chatgpt-search | Display name | Position | | --- | --- | | ClickHouse | 1 | | QuestDB | 4 | ##### 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 Google-ai-mode: Not available Perplexity: Not available Google-ai: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Xai-search: Not available #### Platform rows ##### Google-ai-mode ##### Perplexity | Display name | Position | | --- | --- | | CockroachDB | 5 | ##### Google-ai | Display name | Position | | --- | --- | | CockroachDB | 1 | | PingCAP | 2 | ##### Bing-copilot-search ##### Chatgpt-search ##### 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 Google-ai-mode: Not available Perplexity: Not available Google-ai: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Xai-search: Not available #### Platform rows ##### Google-ai-mode ##### Perplexity | Display name | Position | | --- | --- | | Redis | 1 | ##### Google-ai ##### Bing-copilot-search ##### Chatgpt-search | Display name | Position | | --- | --- | | Redis | 1 | ##### Xai-search ## Top sources ## Response excerpts ## Competitor excerpts | Platform | Competitor name | Excerpt | | --- | --- | --- | | perplexity | SingleStore | SingleStore is the clearest example of an HTAP-oriented system. It combines an in-memory rowstore for low-latency transactional access with a disk-based columnstore for scans and historical analytics; it can query across both in one system. | | bing-copilot-search | ClickHouse | Columnar databases like ClickHouse, Snowflake, BigQuery, and DuckDB can handle mixed OLAP/OLTP workloads, but they excel mainly when analytical queries dominate. | | chatgpt-search | SingleStore | ...\| Database \| Mixed workload strength \| OLTP side \| OLAP side \| Best fit \| \| --- \| --- \| --- \| --- \| --- \| \| SingleStore \| Very strong \| Native in-memory rowstore + transactions \| Disk columnstore \| Applications that genuinely need bot... | | chatgpt-search | ClickHouse | ...deletes, point-query path \| Excellent distributed columnar OLAP \| Real-time analytics + CDC/updating dimensions \| \| ClickHouse \| Moderate \| Inserts/upserts/mutations, but not full OLTP \| Excellent \| Analytics-heavy systems with relatively lig... | | google-ai-mode | Neon | Terraform Registry +1 3. * Neon * IaC Support: Community-maintained/Neon-sponsored Neon Terraform Provider * What you can version-control: Neon projects, compute endpoints, branching structures, database roles, and specific databases. | | google-ai-mode | Supabase | The top-tier developer-focused database platforms with strong IaC integration include: 1. * Supabase * IaC Support: Official [Supabase Terraform Provider](/goto?url=CAESawHrOzAVs7uA4VvfQlkAInqoLvmDDfeN-LziMiZ5rqgrJGBeb83JlK2kdPprYCL... | | perplexity | Neon | For version-controlled database provisioning and configuration, Neon and Supabase are the strongest developer-focused options among the platforms reviewed. | | perplexity | Supabase | For version-controlled database provisioning and configuration, Neon and Supabase are the strongest developer-focused options among the platforms reviewed. | | chatgpt-search | MongoDB | ...\| Platform \| IaC integration \| What you can version-control \| Developer fit \| \| --- \| --- \| --- \| --- \| \| MongoDB Atlas \| Excellent — official Terraform provider \| Projects, clusters, networking, users, backups, integrations, poli... | | chatgpt-search | Supabase | ...— official Terraform provider \| Projects, clusters, networking, users, backups, integrations, policies \| ⭐⭐⭐⭐⭐ \| \| Supabase \| Good — official Terraform provider \| Projects, branches, settings, API/config resources \| ⭐⭐⭐⭐ \| \| Neon \|... | | perplexity | CockroachDB | ## Strong candidates \| Database \| Best fit \| Main trade-off versus single-region \| \|---\|---\|---\| \| CockroachDB \| PostgreSQL-compatible SaaS needing active-active regional deployment, tenant/data locality, and resilient writes \| Cross-region consen... | | google-ai | PingCAP | TiDB (PingCAP) * The Pitch: An open-source, MySQL-compatible hybrid transactional and analytical processing (HTAP) database. | ## Trend Visibility delta: 0 Avg position delta: Not available Citation count delta: 0