Sold by: Cube Dev, Inc.Â
Connect siloed data, drive consistent metrics, and power your AI and analytics with context.
Overview
Cube Cloud is a universal semantic layer for data and app development teams that makes it easy to connect siloed data and create consistent metrics that are accessible to any data consumer-AI, BI, spreadsheets, and embedded analytics. The solution provides unmatched integrations and interoperability, supporting a robust set of deployment options, data connectivity, coding languages, and native APIs so that you can build AI and analytics solutions to fit your unique modern data stack requirements.
With Cube Cloud, business data becomes consistent, accurate, easy to access, and most importantly, trusted. Data engineers and application developers use Cube Cloud's code-first, developer-oriented platform to:
- Organize and govern data from cloud data warehouses into centralized, consistent, and
reusable data models and business definitions.
- Apply software engineering best practices and processes to data management: CI/CD,
isolated environments, and version control with Git integration.
- Use intelligent capabilities like data model code generation and front-end embedded
analytics code generation to increase productivity.
- Optimize query performance and save on cloud data usage with pre-aggregation caching
capabilities.
- Deliver data to any downstream tool via data APIs: SQL, REST, GraphQL, AI, and MDX.
Cube accelerates trusted data-driven decisions, delivering better experiences to employees inside the organization, customers outside the organization, and even machines with our native OpenAI integrations. Build Generative AI experiences with the AI API. For internal BI use cases, Cube Cloud provides a semantic catalog and Generative AI capabilities to simplify discovery, exploration, and access to modeled data and downstream, connected BI content for data analysts and business users. Add unlimited named user accounts to allow anyone to search and reuse trusted data products and perform natural language queries in a simplified, business user friendly interface.
When you choose Cube Cloud on AWS, you can easily integrate with the following AWS services and more:
- Redshift, Athena, Aurora, RDS
- QuickSight
Highlights
- Easily deliver a lightning fast embedded analytics experience to delight your customers
- Sync and connect all your BI tools to drive consistency across your company
- Bring context to your LLMs, AI agents, and bots by adding on a semantic layer
Details
Sold by
Delivery method
Deployed on AWS
Unlock automation with AI agent solutions
Fast-track AI initiatives with agents, tools, and solutions from AWS Partners.
Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/12 months |
|---|---|---|
Premium | Cube Cloud Premium ($10K+ annual minimum commitment) | $10,000.00 |
Enterprise | Cube Cloud Enterprise ($20K+ annual minimum commitment) | $20,000.00 |
Enterprise Premier | Cube Cloud Enterprise ($40K+ annual minimum commitment) | $40,000.00 |
Vendor refund policy
All fees are non-refundable and non-cancellable except as required by law.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA)Â .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
Resources
Vendor resources
Support
Vendor support
Email support services are available from Monday to Friday
support@cube.devÂ
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Updated weekly
By Cube Dev, Inc.
By MicroStrategy, Inc.
By Pyramid Analytics BV
Top
25
In Data Analysis
Top
50
In Financial Services, Business Intelligence & Advanced Analytics
Top
10
In Amazon Redshift, Analytic Platforms
Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
Ease of use
Customer service
Cost effectiveness
Positive reviews
Mixed reviews
Negative reviews
AI generated from product descriptions
Data Modeling
Organize and govern data from cloud data warehouses into centralized, consistent, and reusable data models and business definitions
Query Performance Optimization
Implement pre-aggregation caching capabilities to optimize query performance and reduce cloud data usage
API Connectivity
Support multiple data API protocols including SQL, REST, GraphQL, AI, and MDX for downstream tool integration
Development Workflow
Apply software engineering best practices like CI/CD, isolated environments, and version control with Git integration
AI Integration
Provide native OpenAI integrations and AI API for building generative AI experiences with semantic layer context
AI-Powered Workflow Automation
Utilizes generative AI technology to automate complex data analysis and workflow processes across enterprise environments
Cloud-Native Architecture
Supports microservices and cloud container technologies with RESTful APIs and rich SDKs for flexible development and integration
Semantic Graph Technology
Implements advanced semantic graph infrastructure to enhance data reliability and support both structured and unstructured data analysis
Multi-Source Data Connectivity
Enables connection and blending of diverse data sources including platforms like Snowflake and Databricks
Conversational AI Interface
Provides AI-driven chat technology for interactive data exploration, visualization creation, and complex analytics tasks
Data Integration
Seamless integration with multiple cloud data sources including Amazon Redshift, RDS, EMR, S3, Athena, SAP HANA, and other enterprise databases
Analytics Engine
Cloud-scale in-place analytics that leverages underlying data source capabilities for real-time data access without pre-loading data into platform memory
Machine Learning Capabilities
Embedded machine learning algorithms and scripting for advanced data science and complex business problem analysis
Data Preparation
Automatic data modeling, formula generation, and interactive visualization creation with integrated data science capabilities
Security Framework
Role-based data and content access control with centralized governance, multi-tenancy, and single sign-on authentication mechanisms
Standard contract
No
Customer reviews
0 ratings
0 AWS reviews
|
25 external reviews
Star ratings include only reviews from verified AWS customers. External reviews can also include a star rating, but star ratings from external reviews are not averaged in with the AWS customer star ratings.
Commercial Real Estate
Great for AI applications and general data apps!
Reviewed on Jan 21, 2025
Review provided by G2
What do you like best about the product?
I'm using CubeJS for a lot of data apps on my company and it is really incredible for leveraging data for my applications. I also use CubeJS daily for manual analytics, like taking a look at the charts or copying some data to perform some stronger statistical analysis.
The interface simplicity of consumption for REST APIs is really powerful for integrating in any language and maintaining a standardized consumption around the tech ecosystem.
This can also be used as a "Feature Store" of some sorts, together with the preAggregations layer, for ML and AI applications, making it really really simple to roll them out.
I've already used the Customer Support and their response was really fast and the person helping me was also really proactive.
The ability to test changes to a cube or creating a cube via Git branches is **really powerful**! It really helps!
Finally, implementing cubes, measures, and also configuring dimensions is way too simple: we use it to connect to BigQuery and maintaining the semantics of metrics on CubeJS, which makes it so easy to understand data.
The interface simplicity of consumption for REST APIs is really powerful for integrating in any language and maintaining a standardized consumption around the tech ecosystem.
This can also be used as a "Feature Store" of some sorts, together with the preAggregations layer, for ML and AI applications, making it really really simple to roll them out.
I've already used the Customer Support and their response was really fast and the person helping me was also really proactive.
The ability to test changes to a cube or creating a cube via Git branches is **really powerful**! It really helps!
Finally, implementing cubes, measures, and also configuring dimensions is way too simple: we use it to connect to BigQuery and maintaining the semantics of metrics on CubeJS, which makes it so easy to understand data.
What do you dislike about the product?
I still think documentation is a bit confusing for some features.
I've faced some issues with preAggregations where some measuers were they were being summed instead of being averaged over for `avg` types. Some logic for the `rollup` timeout is a bit confusing.
Although the REST API interface doens't really need any framework, I feel that a simple SDK providing the objects for serialization would be nice to have.
Some more complex charts in the Playground would also be nice to have, together with a simple export like CSV/JSON from the Playground (I do understand that the Playground is... a Playground... but sometimes I use it as an analytics tool to fetch some informations).
I think that we also lack a propert LSP (or a type checker) for Cube on Javascript. Sometimes I makes some mistakes that are related to Cube JS syntax (use of AI on the Code Editor also makes it more prone to error). This would be really helpful. Some features can only be tested once in production (like preAggregations syntax), which makes it a bit harder to integrate.
I've faced some issues with preAggregations where some measuers were they were being summed instead of being averaged over for `avg` types. Some logic for the `rollup` timeout is a bit confusing.
Although the REST API interface doens't really need any framework, I feel that a simple SDK providing the objects for serialization would be nice to have.
Some more complex charts in the Playground would also be nice to have, together with a simple export like CSV/JSON from the Playground (I do understand that the Playground is... a Playground... but sometimes I use it as an analytics tool to fetch some informations).
I think that we also lack a propert LSP (or a type checker) for Cube on Javascript. Sometimes I makes some mistakes that are related to Cube JS syntax (use of AI on the Code Editor also makes it more prone to error). This would be really helpful. Some features can only be tested once in production (like preAggregations syntax), which makes it a bit harder to integrate.
What problems is the product solving and how is that benefiting you?
CubeJS helps me solve the issue of integrating data from multiple sources to Applications: from general software to AI-powered applications, CubeJS allows us to have low latency data fetching and only worrying with what to do with the data.
Rafael L.
What a modern semantic layer solution should look like
Reviewed on Oct 09, 2023
Review provided by G2
What do you like best about the product?
Using CubeJS Cloud to build our semantic layer has been great! It really just takes a lot of development effort off our shoulders. This is especially great for small teams that don't have DevOps engineers available to help create and monitor a platform. The development and maintenance have been simple to maintain. Their support is also great where I could solve a build issue with a live chat in a short time. There are many features including different endpoints to consume data, which makes embedding analytics into our product straightforward.
What do you dislike about the product?
I still feel that integration with BI tools is not totally straightforward yet, some query aggregations fail and require some tweaks. I still have to test the new "Semantic Layer Sync" feature. Also, a thing that was very great about dbt metrics that I miss here in CubeJS is the ability to create a new metric based on other metrics as long as they have the same time granularity, CubeJS could find a way to implement something flexible as this as well.
What problems is the product solving and how is that benefiting you?
We use all major features: serving metrics on endpoints, embedded analytics in our product front-end, and feed BI tools.
Research
Easy to setup analytics
Reviewed on Sep 21, 2023
Review provided by G2
What do you like best about the product?
- declarative schema definitions make it easy to built UI interfaces on top of your data
- built-in cache
- extensibility through express middlewares
- great slack community
- easy to get setup
- built-in cache
- extensibility through express middlewares
- great slack community
- easy to get setup
What do you dislike about the product?
we ran into an issue with cube cloud processes restarting too frequently which meant the entire schema needed to be reloaded on subsequent requests which took nearly 5s and triggered our latency alarms. luckily due to cube's extensibility we were able to implement a custom express middleware to trigger loading of the schema when the instance started up which worked around the problem for us.
the schema compiler is a little quirky and has too much magic which makes it a little more difficult to define schemas in typescript, but not insurmountable.
personally I don't like the online schema editor since we discourage folks from making changes outside of the version control. I wish we could have disabled this feature.
out-of-the-box scripts to scaffold out schemas would be nice. we ended up rolling our own.
cube-sql is interesting, but the lack of ability to do basic math in queries made it unusable for us.
the schema compiler is a little quirky and has too much magic which makes it a little more difficult to define schemas in typescript, but not insurmountable.
personally I don't like the online schema editor since we discourage folks from making changes outside of the version control. I wish we could have disabled this feature.
out-of-the-box scripts to scaffold out schemas would be nice. we ended up rolling our own.
cube-sql is interesting, but the lack of ability to do basic math in queries made it unusable for us.
What problems is the product solving and how is that benefiting you?
Cube makes it easy to build analytics tools on your data.
Information Technology and Services
Great Data-Driven Applications
Reviewed on Sep 21, 2023
Review provided by G2
What do you like best about the product?
Cube.js has been a game-changer in my development journey, offering an incredible solution for building data-driven applications. With its intuitive data modeling capabilities, I've been able to structure data in a way that truly suits my application's needs. it handles data efficiently, ensuring that my users can explore insights seamlessly.
What do you dislike about the product?
Cube.js, like any tool with advanced capabilities, has a learning curve. Beginners may find it challenging to grasp all the concepts, especially when dealing with complex data models and SQL queries. However, Cube.js does provide documentation and tutorials to help mitigate this issue.
What problems is the product solving and how is that benefiting you?
Cube.js simplifies complex data modeling by providing a structured way to define cubes, dimensions, and measures. This makes it easier to represent and work with your data, allowing you to create meaningful analytics without getting lost in complex SQL queries or data transformations.
Mateusz J.
Totally must-have for modern data analysis systems
Reviewed on Jul 25, 2023
Review provided by G2
What do you like best about the product?
Easy to make pre-aggregations that are a game-changer in modern data analysis systems, as they are a main layer for best in class optimization. Ease of configuration and deployment was a key for me.
What do you dislike about the product?
I miss a local/system native optimization program like cloud platform panel - possibility to write preaggs and already check them before deployment, analyze queries and requests to optimize my application even more at data layer. That would be an excellent improvement for general DX (Developer Experience) as well.
What problems is the product solving and how is that benefiting you?
I'm untangling data for decision-makers in various companies. One of my customers already got an 2-3 times increased sales because they got critical data and trends right now.