AI Visibility Audit
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Prepared by saigon.digital · June 2026
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Your buyers aren't just Googling "best distributed database" anymore — they're asking ChatGPT, Perplexity, and Gemini which database to choose for their next multi-region deployment. This audit shows exactly where CockroachDB stands, who's winning, and what to do next.
Saigon Digital transformed how Ski.com shows up online. Beyond rebuilding our platform, they helped us rethink our entire search and AI visibility strategy. We saw a significant uplift in organic traffic, our content started appearing in AI-generated travel recommendations, and the quality of inbound leads improved dramatically. They understand where digital discovery is heading and how to turn visibility into real commercial results.
See how we've helped brands grow. Read our case studies and learn more about what we do.
View Case StudiesA snapshot of where Cockroach Labs stands in the AI search era — and how hyperscaler-backed competitors are reshaping the narrative around distributed SQL databases.
CockroachDB is trusted by DoorDash, NVIDIA, OpenAI, and Booking.com — powering mission-critical infrastructure at global scale. With a Domain Rating of 78, 3,184 organic keywords, and 52,000 monthly organic visits, Cockroach Labs has strong SEO fundamentals. But the way CTOs and platform engineers discover database solutions has fundamentally changed. When they ask ChatGPT, Google AI, or Perplexity "what's the best distributed database for multi-region deployment?", Google Cloud Spanner and Amazon Aurora DSQL consistently appear first — backed by the near-infinite domain authority of their parent companies (DR 96+). Despite building a category-defining product, CockroachDB is losing high-intent buyer queries to hyperscaler-backed competitors whose parent domains carry 20+ DR points more. The gap isn't product quality — it's that AWS and Google are outpacing you in the AI content layer that increasingly drives enterprise purchasing decisions.
We tested how CockroachDB appears when potential buyers ask AI tools to recommend distributed SQL databases for enterprise and multi-region use cases. Here's what we found.
ChatGPT consistently recommends CockroachDB for distributed SQL and multi-region queries, citing its PostgreSQL compatibility and serializable isolation. However, Google Cloud Spanner and Amazon Aurora frequently appear above CockroachDB in ranked lists.
CockroachDB appears in 2 of 4 tested Google AI Overview queries. For "best distributed SQL database" it's prominently featured, but for "most reliable multi-region database" and "horizontal scaling SQL", hyperscaler products and open-source alternatives dominate.
Perplexity cites CockroachDB for category-specific queries but frequently prioritises Google Cloud Spanner and Aurora DSQL for managed/serverless database queries. YugabyteDB's aggressive comparison content also competes for Perplexity citations.
Gemini shows a noticeable bias toward Google Cloud Spanner for distributed SQL queries. CockroachDB appears in broader "best distributed databases" lists but is frequently positioned below Google's own offering in Gemini's recommendations.
2 / 4 platforms consistently cite CockroachDB in relevant AI-generated recommendations. You have strong brand recognition but are losing ground on managed/serverless and multi-region deployment queries where hyperscaler-backed alternatives dominate.
Updated "CockroachDB vs Aurora DSQL" and "CockroachDB vs Cloud Spanner" head-to-head pages with 2026 benchmark data, structured FAQ schema on all product and pricing pages, a definitive "Best Distributed SQL Databases" guide owned by CockroachDB, expanded third-party validation through analyst reports, and developer community content that reinforces CockroachDB Cloud as the managed alternative to hyperscaler offerings.
We ran the exact searches your prospective buyers use when asking AI tools to recommend a distributed SQL database for enterprise deployments. Here's who appeared — and whether CockroachDB was in the answer.
CockroachDB appears in 2 of 4 tested buyer queries — specifically for "distributed SQL" and "cloud native database" category terms where it has strong brand association. But for "multi-region deployment" and "horizontal scaling SQL" queries, hyperscaler products (Aurora, Spanner) and open-source alternatives (TiDB, YugabyteDB) dominate. The concerning pattern: CockroachDB is strongest on category-level queries but is being displaced on the specific capability queries that high-intent enterprise buyers actually use when evaluating solutions.
CockroachDB's real-world credentials — powering NVIDIA, OpenAI, DoorDash, and Booking.com across multi-region deployments — are exactly what AI models want to reference for capability-specific queries. The gap is that this proof isn't structured in AI-extractable formats for queries about "reliability", "horizontal scaling", and "multi-region". Publishing benchmark-rich, structured content targeting these specific capability narratives can close the gap and reclaim queries where CockroachDB has the strongest real-world evidence but weakest AI visibility.
These are the platforms currently winning AI recommendations in your market. Understanding why they're cited — and where CockroachDB falls short — reveals the exact gap to close.
| Company | DR | ChatGPT | Google AIO | Perplexity | Why They Win |
|---|---|---|---|---|---|
| CockroachDB You | 78 | Cited | Partial | Partial | Audit target |
| Google Cloud Spanner | 96* | Cited | Appearing | Cited | Backed by google.com's domain authority (DR 96). "Fully managed" and "serverless" positioning aligns perfectly with how AI models categorise modern databases. Google's own infrastructure narrative gives Spanner unmatched credibility signals in AI-generated recommendations. |
| Amazon Aurora DSQL | 97* | Cited | Appearing | Cited | AWS ecosystem dominance (DR 97) means Aurora inherits massive authority. "99.999% multi-region availability" and "serverless" messaging is optimised for AI extraction. Every AWS documentation page, tutorial, and partner blog reinforces Aurora's visibility. |
| YugabyteDB | 72 | Partial | Partial | Partial | Aggressive "YugabyteDB vs CockroachDB" comparison content with benchmark data. 100% open-source positioning. Publishes detailed PostgreSQL compatibility scores (85% vs CockroachDB's 54%) — content AI models extract frequently. |
| PlanetScale | 78 | Partial | Partial | Cited | Strong developer community engagement and Vitess-backed MySQL compatibility. 99.999% SLA for multi-region. Active on Hacker News, Reddit, and developer blogs — platforms that Perplexity heavily indexes for tech recommendations. |
| TiDB (PingCAP) | 75 | Partial | Partial | Partial | HTAP differentiator (combined OLTP + OLAP) with MySQL compatibility. Publishes "Best Distributed SQL Databases" guides ranking themselves #1. Strong presence in Asia-Pacific market where CockroachDB has less content footprint. |
Badge key: Cited Partial Not Cited DR scores from Ahrefs API (June 2026). *Parent domain DR for cloud-hosted products.
These are the highest-leverage changes Cockroach Labs can make right now to reclaim AI recommendations and close the hyperscaler visibility gap.
Comparison content is the #1 format AI models extract for recommendation queries. CockroachDB has existing comparison pages, but they need refreshing with 2026 "Performance Under Adversity" benchmark data, structured FAQ schema, and clear messaging around CockroachDB's advantages: cloud-agnostic deployment, no vendor lock-in, and serializable isolation without the hyperscaler premium. AI models prioritise recent, structured, benchmark-backed comparisons — and your existing "Performance Under Adversity" framework is a powerful differentiator that no hyperscaler can replicate.
TiDB (PingCAP) currently owns the top-ranking "Best Distributed SQL Databases" guide and positions TiDB first. CockroachDB should publish its own authoritative, honest comparison guide covering Aurora DSQL, Cloud Spanner, YugabyteDB, TiDB, and PlanetScale — with structured data markup, real-world performance data, and use-case recommendations. AI models favour content from actual industry participants who demonstrate deep expertise and cite verifiable benchmarks. This is a category-defining content play.
CockroachDB is invisible in AI results for "most reliable database for multi-region cloud deployment" and "horizontal scaling SQL" queries — despite being purpose-built for exactly these use cases. Creating dedicated landing pages with customer case studies (DoorDash's multi-region architecture, Booking.com's global deployment), structured FAQ schema, and "how CockroachDB handles" technical explainers for each capability gives AI models the specific signals needed to cite CockroachDB for these high-intent queries.
This audit shows the problem. We have a clear strategy to fix it — and results typically show within the first 60 days of engagement.
CockroachDB powers mission-critical systems for 70+ billion-dollar enterprises across 40 countries. You've built the category-defining distributed SQL database — now you need the AI-optimised content layer that ensures every CTO and platform engineer who asks an AI tool "which database should I choose?" sees CockroachDB at the top. We've helped SaaS and enterprise technology brands close exactly this gap. A 30-minute call is all it takes to map out a plan.
Nick Rowe · CEO & Co-Founder, Saigon Digital
Full GEO strategy, hyperscaler competitor content audit, structured data implementation, "CockroachDB vs" comparison content programme, authority-building through developer community engagement, and monthly AI visibility tracking — all focused on making CockroachDB the #1 AI recommendation for distributed SQL databases.
CockroachDB's strong foundation — DR 78, 7,322 referring domains, 88K+ backlinks, and a world-class customer roster — means results can compound quickly. Initial AI citation improvements within 45–60 days. Full competitive visibility against hyperscaler-backed alternatives typically achievable in 90–120 days with consistent content investment.
Amazon Aurora DSQL launched in 2025 and is aggressively capturing the "distributed SQL" narrative with AWS's marketing machine. YugabyteDB is publishing benchmark comparisons that directly challenge CockroachDB's position. Every month these competitors publish more AI-extractable content, their position compounds. CTOs and platform engineers are increasingly asking AI "which distributed database should I choose?" — and right now, the answer isn't always CockroachDB.