GX Cloud
GX Cloud is a fully managed SaaS data quality platform built on the open-source Great Expectations framework.
Publisher review
GX Cloud is a fully managed SaaS data quality platform built on the open-source Great Expectations framework. It is designed for data engineering and analytics teams that need to validate data at scale without managing infrastructure. The service is easy to set up and delivers results quickly, enabling both technical and non-technical users to define data quality tests—called Expectations—in plain language.
GX Cloud automates coverage for data quality by running validations against data assets in databases and warehouses, and it supports multi-tenancy, multi-environment deployments, and scalable performance optimization. Pricing is based on the number of Data Assets actively under test per month, with the free Developer plan allowing up to 5 Data Assets and 3 users, the Team plan supporting up to 10 users with custom Data Asset limits, and the Enterprise plan offering custom limits and additional features like SSO, uptime SLA of 99.5%, and dedicated support. GX Cloud stores only metadata and validation results, not the underlying data, and provides secure encrypted storage with multi-region data residency options.
It competes with Monte Carlo and Acceldata, but is more focused on declarative quality rules (Expectations) rather than full-stack observability. A key trade-off is that GX Cloud does not offer real-time monitoring or pipeline-level lineage out of the box; it is a batch-oriented validation tool. Additionally, the free tier is limited to 5 Data Assets and 3 users, which may constrain larger teams.
The platform relies on the GX Core engine, which can be resource-intensive for very large datasets if not tuned. Finally, while GX Cloud simplifies collaboration, it requires users to adopt the Expectation pattern, which may have a learning curve for teams accustomed to ad-hoc SQL checks.
How it works
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Fully managed SaaS
No infrastructure to manage; GX Cloud handles scaling, security, and updates automatically.
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Plain language Expectations
Define data quality rules using simple, readable statements instead of complex code.
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Automated validation coverage
Schedule and run validations across data assets to catch issues before they impact downstream consumers.
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Multi-tenancy support
Organize workspaces and users within a single account, enabling team isolation and collaboration.
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Multi-region data residency
Store validation metadata in chosen geographic regions to comply with data governance requirements.
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Unlimited Expectations and rows
Paid plans allow unlimited tests and unlimited rows per data asset, so volume does not increase cost.
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AI-enabled recommendations
Limited AI suggestions help users create relevant Expectations based on data patterns.
Strengths and trade-offs
Strengths
- Free Developer plan supports up to 5 Data Assets and 3 users, making it accessible for small teams and prototypes.
- All paid plans include unlimited Expectations (tests) and unlimited rows per Data Asset, removing cost concerns for large datasets.
- Uptime SLA of 99.5% on paid plans ensures reliable availability for production validation pipelines.
- Secure encrypted storage with multi-region data residency options meets enterprise compliance requirements.
Trade-offs
- Free tier is limited to 5 Data Assets and 3 users, which may be restrictive for growing teams or multi-project use.
- GX Cloud is a batch validation tool, not a real-time observability platform; it does not monitor streaming data or pipeline lineage.
- Relies on the GX Core engine, which can be resource-intensive for very large datasets without careful tuning.
- Requires teams to adopt the Expectation pattern, which may have a learning curve for those used to ad-hoc SQL checks or other quality tools.
Pricing context
Free Developer tier (up to 5 Data Assets, 3 users); Team and Enterprise plans have custom pricing based on Data Asset count and user limits, with Team supporting up to 10 users and Enterprise offering unlimited users, SSO, 99.5% uptime SLA, and dedicated support.
Getting started with GX Cloud
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Sign up for GX Cloud
Go to the GX Cloud website and click the Get Started button. Choose the free Developer plan to create your account. Enter your email, set a password, and verify your email address to activate your workspace.
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Connect your data source
In the GX Cloud dashboard, navigate to the Data Assets section and click Add Data Asset. Select your database or warehouse type, then provide the connection details such as host, port, and credentials. Test the connection to confirm it works.
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Define your first Expectation
Open the Expectations tab and click Create Expectation. Write a plain language rule, such as 'column A values must be greater than 0'. Save the Expectation to apply it to your selected data asset.
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Run a validation
Go to the Validations page and click Run Validation. Choose the data asset and the Expectation you defined. GX Cloud will execute the check and display pass/fail results along with any anomalies detected.
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Schedule recurring validations
In the Schedules section, click Create Schedule. Set the frequency (e.g., daily or hourly) and select the data assets and Expectations to include. Enable the schedule to automate ongoing data quality checks.
Frequently Asked Questions
What is GX Cloud and how does it work?
GX Cloud is a fully managed SaaS data quality platform built on the open-source Great Expectations framework. It lets data teams define quality tests called Expectations in plain language, then automatically runs validations against data assets in databases and warehouses without managing infrastructure.
What are the pricing plans for GX Cloud?
GX Cloud offers a free Developer plan with up to 5 Data Assets and 3 users. The Team plan supports up to 10 users with custom Data Asset limits, while the Enterprise plan provides unlimited users, SSO, a 99.5% uptime SLA, and dedicated support. All paid plans include unlimited Expectations and rows.
What are the main features of GX Cloud?
Key features include fully managed SaaS with no infrastructure to manage, plain language Expectations for defining data quality rules, automated validation coverage, multi-tenancy support, multi-region data residency, unlimited Expectations and rows on paid plans, and AI-enabled recommendations for creating relevant tests.
What are the strengths and weaknesses of GX Cloud?
Strengths include a free Developer plan, unlimited Expectations and rows on paid plans, a 99.5% uptime SLA, and secure encrypted storage with multi-region options. Weaknesses are the free tier's 5 Data Asset limit, batch-only validation without real-time monitoring, resource-intensive GX Core engine, and a learning curve for Expectation patterns.
How does GX Cloud compare to Monte Carlo?
GX Cloud focuses on declarative quality rules called Expectations for batch validation, while Monte Carlo offers full-stack observability including real-time monitoring and pipeline lineage. GX Cloud is more suited for teams wanting a simple, code-free data quality tool, whereas Monte Carlo targets broader data reliability needs.
Is GX Cloud suitable for large teams or enterprises?
GX Cloud can suit large teams with its Enterprise plan offering unlimited users, SSO, and a 99.5% uptime SLA. However, the free tier limits to 3 users and 5 Data Assets, and the batch-oriented design may not meet real-time monitoring needs. Teams must adopt Expectation patterns, which may require training.
Alternatives
How GX Cloud compares
Direct head-to-head against 3 competitors. Picked by 7wData.
GX Cloud
- Pricing
- Free Developer tier (up to 5 Data Assets, 3 users); Team and Enterprise plans have custom pricing based on Data Asset count and user limits, with Team supporting up to 10 users and Enterprise offering unlimited users, SSO, 99.5% uptime SLA, and dedicated support.
- Target
- GX Cloud is a fully managed SaaS data quality platform built on the open-source Great Expectations framework.
- Strength
- Free Developer plan supports up to 5 Data Assets and 3 users, making it accessible for small teams and prototypes.
- Watch for
- Free tier is limited to 5 Data Assets and 3 users, which may be restrictive for growing teams or multi-project use.
Great Expectations (GX Core)
- Pricing
- Free open source; GX Cloud Developer free, Team/Enterprise custom
- Target
- Data teams needing open-source data quality framework
- Deployment
- Self-hosted or GX Cloud SaaS
- Strength
- Open-source Python library with 10k+ GitHub stars
- Watch for
- Cloud pricing is custom only; open-source requires self-management
dbt Cloud
- Pricing
- Free for solo devs; Team $100/mo; Enterprise custom
- Target
- Analytics engineers focused on data transformation and testing
- Deployment
- SaaS or self-hosted (dbt Core)
- Strength
- Built-in data testing and documentation alongside transformations
- Watch for
- Pricing escalates with compute usage; testing is secondary to transforms
Monte Carlo
- Pricing
- Custom/Contact sales (usage-based)
- Target
- Enterprise data teams needing end-to-end observability
- Deployment
- SaaS with agent-based deployment
- Strength
- Automated data lineage and incident alerting
- Watch for
- No free tier; pricing opaque and scales with data volume
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