CloudQuery

CloudQuery is an open-source ELT platform that syncs cloud infrastructure and SaaS metadata from over 100 sources into SQL-queryable data warehouses under your control.

Reviewed by 7wData

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CloudQuery is an open-source ELT platform that syncs cloud infrastructure and SaaS metadata from over 100 sources into SQL-queryable data warehouses under your control. Founded in 2021, the San Francisco–based company has raised $34.5M and counts Fastly, Zendesk, Reddit, and Palo Alto Networks among its named customers. The core product runs as a self-hosted agent (Docker, Kubernetes, or binary) that continuously mirrors state from cloud providers (AWS with 200+ tables, GCP, Azure, Kubernetes) and SaaS platforms (Okta, GitHub, Cloudflare, Slack, Datadog) into your warehouse (PostgreSQL, Snowflake, BigQuery, Redshift, DuckDB, S3).

What sets CloudQuery apart is historical drift detection—it tracks changes over time, enabling governance-as-code, compliance automation, and continuous monitoring. The tool is especially popular with cloud engineering, security, and FinOps teams who need multi-cloud visibility, audit trails, and CIS benchmark monitoring. However, pricing is opaque (sales-required quotes only, no public tiers), configuration requires YAML and DevOps maturity, and the ecosystem is smaller than general-purpose ELT tools.

A June 2025 merger with env zero (a GitOps platform) leaves integration roadmaps unclear. CloudQuery is MPL-2.0 licensed, meaning the code is open and auditable, but enterprise features and advanced support are commercial.

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How it works

  1. 100+ cloud and SaaS integrations

    AWS (200+ tables including EC2, S3, IAM, Lambda), GCP, Azure, Kubernetes, Okta, GitHub, Cloudflare, Slack, Datadog, and 70+ more SaaS platforms. Coverage grows via community plugins and Yevgeny Pats's roadmap announcements.

  2. SQL-queryable normalized warehouse

    Synced data lands as standardized tables in PostgreSQL, Snowflake, BigQuery, Redshift, DuckDB, or S3. Users write SQL for governance, cost analysis, and compliance, not API scripts.

  3. Historical drift detection

    Stores snapshots over time, letting users identify when infrastructure changed, who created a resource, or when a security group rule was added—unique compared to one-time-snapshot tools like Steampipe.

  4. Governance-as-code

    Write YAML-based policies that run continuously against synced data. Automatically flag non-compliant resources (e.g., unencrypted buckets, public security groups) and wire to ticketing or remediation workflows.

  5. Self-hosted architecture with optional SaaS layer

    Run the agent on your VPC or Kubernetes cluster; data never leaves your warehouse. Optional CloudQuery Platform SaaS adds RBAC, SSO, audit logs, and multi-user orchestration for enterprise teams.

  6. Event-based real-time sync

    For select sources (AWS, GCP), CloudQuery can subscribe to event streams (CloudTrail, Pub/Sub) and update the warehouse in near real-time, not just on scheduled snapshots.

  7. Open-source with MPL-2.0 license

    5,800+ GitHub stars, 22,000+ commits. Source is auditable and deployable without vendor lock-in. MPL-2.0 is copyleft but permits modification; less restrictive than GPL, more protective than MIT.

Strengths and trade-offs

Strengths

  • Multi-cloud inventory in a single warehouse eliminates cloud-specific dashboards; teams query all AWS, GCP, Azure data with SQL.
  • Historical drift detection catches security drift (e.g., when a security group was modified) and cost drift (idle resources), not just current state.
  • Self-hosted with data in user's warehouse avoids vendor lock-in and meets strict data residency or compliance rules (HIPAA, PCI-DSS, GDPR).

Trade-offs

  • Pricing is opaque (no published tiers); sales-required quotes create budget uncertainty and slow evaluation cycles, a documented friction point for mid-market prospects.
  • Configuration is YAML-heavy and requires DevOps expertise; onboarding is steeper than managed ELT tools, limiting appeal to non-technical teams.
  • Community is smaller (5.8k GitHub stars vs. Airbyte's 15k); fewer third-party resources and integrations rely on community maintenance, which can lag.
  • June 2025 env zero merger leaves product roadmap unclear; potential pivot to GitOps-first positioning may shift priorities away from pure data sync use cases.

Pricing context

CloudQuery's pricing is usage-based (charged per synced row annually) but not publicly disclosed; all quotes require sales contact. The free open-source CLI is available for non-production use and lab environments. Enterprise tier includes dedicated support, SLAs, and custom integrations. The lack of published pricing tiers is a recurring complaint in independent reviews; competitors like Steampipe publish rates openly, making comparison difficult for budget forecasting.

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Sources

Reporting on this tool draws on these publicly available sources.

  1. www.cloudquery.io — Company website, product overview, founding year (2021), headquarters (San Francisco)
  2. github.com — 5,800+ GitHub stars, 22,000+ commits, MPL-2.0 license, open-source status and active development
  3. www.g2.com — Verified customer reviews citing multi-cloud governance, SQL ownership, pricing opacity, and compliance use cases
  4. www.crunchbase.com — $34.5M total funding ($3.5M Seed 2021, $15M Series A 2022, $16M strategic 2025), named customers (Fastly, Zendesk, Reddit, Palo Alto Networks)
  5. aws.amazon.com — Third-party validation of multi-cloud data-lake use case and CloudQuery integration patterns
  6. news.ycombinator.com — Hacker News community early discussion (2020–21) of multi-cloud visibility and provider coverage sentiment
  7. www.cloudquery.io — June 2025 merger announcement with env zero, GitOps integration roadmap
  8. docs.cloudquery.io — 100+ source integrations including AWS (200+ tables), GCP, Azure, Kubernetes, 70+ SaaS platforms