+
+
Visit Website

About

BigQuery is a serverless, multicloud data warehouse that simplifies the process of working with all types of data so you can focus on getting valuable business insights quickly. At the core of Google’s data cloud, BigQuery allows you to simplify data integration, cost effectively and securely scale analytics, share rich data experiences with built-in business intelligence, and train and deploy ML models with a simple SQL interface, helping to make your organization’s operations more data-driven. Gemini in BigQuery offers AI-driven tools for assistance and collaboration, such as code suggestions, visual data preparation, and smart recommendations designed to boost efficiency and reduce costs. BigQuery delivers an integrated platform featuring SQL, a notebook, and a natural language-based canvas interface, catering to data professionals with varying coding expertise. This unified workspace streamlines the entire analytics process.

About

Domo puts data to work for everyone so they can multiply their impact on the business. Our cloud-native data experience platform goes beyond traditional business intelligence and analytics, making data visible and actionable with user-friendly dashboards and apps. Underpinned by a secure data foundation that connects with existing cloud and legacy systems, Domo helps companies optimize critical business processes at scale and in record time to spark the bold curiosity that powers exponential business results.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Organizations in need of a powerful, serverless, multicloud, AI-enabled data warehouse that simplifies the process of working with all types of data

Audience

Customers in all industries looking to manage their business from a single platform.

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free ($300 in free credits)
Store 10 GiB of data and run up to 1 TiB of queries for free per month. New customers also get $300 in free credits to try BigQuery and other Google Cloud products.

No automatic charges. You only start paying if you decide to activate a full, pay-as-you-go account or choose to prepay. You’ll keep any remaining free credit.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 4.7 / 5
ease 4.7 / 5
features 5.0 / 5
design 4.7 / 5
support 4.7 / 5

Reviews/Ratings

Overall 4.6 / 5
ease 4.6 / 5
features 4.4 / 5
design 4.5 / 5
support 4.1 / 5

Pros from Real Users

Pros

  • It scales to handle massive datasets with petabyte scale query processing. Fast performance with results in seconds regardless of data size. Intuitive SQL interface familiar for analysts.
  • BigQuery, as Google's fully-managed, serverless data warehouse, has been a standout solution in the world of large-scale data analysis. Its most striking feature is the impressive speed with which it processes vast datasets. Leveraging the power of Google's advanced cloud infrastructure, BigQuery offers near real-time execution of complex SQL queries, a boon for businesses and analysts dealing with big data. The scalability of BigQuery is another significant advantage. It adeptly adjusts to varying data volumes without necessitating active management of the underlying infrastructure. This feature is particularly valuable for businesses experiencing variable data loads. Additionally, its user-friendly interface, coupled with seamless integration with other Google Cloud services, simplifies the data management process, making it accessible to a wide range of users.
  • A very scalable serverless data warehouse is Google Cloud BigQuery. Large datasets are handled by it automatically, guaranteeing excellent performance without the need for user involvement.

Pros & Cons from Real Users

Pros

  • Domo is a software that is great to have because of its amazing implementation and configuration of the data. It is currently a software with many capabilities that help understand the data in an efficient way in the form of graphs and reports that are easy to read. There are many tools that are great to use in Domo, but the most relevant ones definitely are, firstly, is the reporting capabilities that the software has, it allows us to have constant insights on our data in real time, because these can be automated and delivered to our team at the right time without us needing to generate each report individually, the software takes care of this aspect which is something I enjoy a lot. It is possible to have the reports be customized and shown in different ways than the usual report and that aspect is helpful to make the reports more intuitive and make better presentations of these in order to reach more people to understand the data. Secondly, I like the fact that Domo prioritizes security over anything else, it has the option to limit access to those members who are not allowed to see different kinds of information and provides a sense of hierarchy that every business should have, it is easy to customize access and provide things like passwords to different data files that are stored in the software; additionally, the data is encrypted so we can use the software peacefully without feeling scared of losing anything or getting hacked and getting all our precious and vital information robbed, a business is just like a human and we can't treat the data lightly, we should be careful and choose a nice software that will care for it. Thirdly, because it updates in real time and we are constantly getting reports on it, Domo has the ability to send out notifications via email and devices to know when the data has changed, this allows us to pay more attention to the changes that happen inside our business and how the metrics are changing in a bad or good way, allowing us to respond to these changes very quickly and not miss out any important event that might be happening, these alerts are very customizable and can be set for every type of data or only set it up for specific data, which makes it even better as we are able to be aware of our own projects that we are working on and each member can be only aware of what they need to be aware of without any distractions or unimportant data to them crowding their notifications and dashboard, it is an useful tool that I find myself using a lot just to keep track of my own projects inside the business.
  • Complete flexibility to analyse data in so many ways and formats. Accessibility to share tools and solutions across our business.
  • Easy to build cards. Sumo cards are super useful to analyze large amounts of data, Upsert is a great feature and very helpful with SAP BW as a source system.
  • Domo is extremely easy to use and has become an integral part of our day to day. It adds the ability to combine datasets from lots of different locations and datatypes into one seamless dataset that gives a holistic view.
  • Domo takes all the power of traditional SQL based reporting and makes it so that anyone with decent Excel experience can quickly get into the weeds of their data. Magic ETL 2.0 is intuitive, powerful, and extremely fast. Card building is as easy as building a pivot table in Excel with near unlimited ability to customize.

Cons

  • In my opinion, Domo still has a long road to go before becoming an exceptional software. This is because I find that the graphical part of the software is not as developed as it needs to be and they should really include more options when it comes to the creation of graphs to include more analytical power and more organized data into the graphs. For me, Domo lacks in this area and the tools are not really optimized for the customization of the graphs, it is a bit limited and it does not feel like they are taking advantage of the possibilities that the software has, it is capable of doing so much more but as of right not they have not updated and improved the creation of the graphs, I would like to have total control over the data and display it in a way that is more advantageous and use different data to build different sets of graphs that work together in a comparative way, it is an essential need to have this kind of tool but Domo only offers limited tools that do not go very far than providing only the superficial aspects of a graphical software, it would be good to go in so much more depth and upgrade the graphs tools to provide a better experience for the users and ensure that the data is being analyzed the right way. Also, it takes a good bandwidth connection to be able to use the software, usually we do have a good bandwidth connection so it does not present as an issue to us, but I think that it would be really nice if it could be optimized to be able to be used in a not so good connection, that way if we happen to use Domo on the go and we don't have a good connection as in our workplace, we can still use and create graphs.
  • Finding where to get started among all of the options!
  • Disappointed that it cant handle incremental (Delta) loads. But now with UPSERT, it is no more a concern.
  • We work very closely with several other organizations and transferring dashboards and datasets between organizations to avoid reinventing the wheel is extremely cumbersome and time-consuming.
  • One feature that I have yet to find in Domo is the ability to see the underlying SQL being written based on the Magic ETL work that you are doing. I believe this would take it to another level and give people with less SQL experience a chance to learn what their drag and drop approach is really doing behind the scenes.

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Google
Founded: 1998
United States
cloud.google.com/bigquery

Company Information

Domo
Founded: 2011
United States
www.domo.com

Alternatives

Alternatives

Looker

Looker

Google

Categories

Google Cloud BigQuery integrates seamlessly with AI and machine learning tools to perform data analytics on vast datasets. By offering advanced capabilities for building and running machine learning models directly within the platform, users can take full advantage of Google’s AI services. It allows businesses to leverage data for predictive analytics, enabling smarter decision-making processes. New customers get $300 in free credits to explore BigQuery’s AI-driven features, which can help them unlock valuable insights without any upfront costs, making it easy to experiment with machine learning models and data exploration. This integration positions BigQuery as a powerful tool for organizations looking to harness AI for data-driven innovation and growth.

BigQuery is designed to handle and analyze big data, making it an ideal tool for businesses working with massive datasets. Whether you are processing gigabytes or petabytes, BigQuery scales automatically and delivers high-performance queries, making it highly efficient. With BigQuery, organizations can analyze data at unprecedented speed, helping them stay ahead in fast-moving industries. New customers can leverage the $300 in free credits to explore BigQuery's big data capabilities, gaining practical experience in managing and analyzing large volumes of information. The platform’s serverless architecture ensures that users never have to worry about scaling issues, making big data management simpler than ever.

BigQuery is a powerful platform for business intelligence (BI) that enables users to perform complex data queries on large datasets. It integrates with various BI tools, providing flexibility to generate actionable insights through intuitive dashboards and reports. By leveraging Google Cloud’s native BI capabilities, businesses can make faster, data-driven decisions with greater confidence. New customers can utilize their $300 in free credits to evaluate BigQuery’s potential for BI purposes and begin transforming raw data into meaningful, decision-supportive reports. This helps businesses uncover trends, measure performance, and develop strategies based on real-time data analysis.

BigQuery is a columnar database that stores data in columns rather than rows, a structure that significantly speeds up analytic queries. This optimized format helps reduce the amount of data scanned, which enhances query performance, especially for large datasets. Columnar storage is particularly useful when running complex analytical queries, as it allows for more efficient processing of specific data columns. New customers can explore BigQuery’s columnar database capabilities with $300 in free credits, testing how the structure can improve their data processing and analytics performance. The columnar format also provides better data compression, further improving storage efficiency and query speed.

BigQuery offers high-performance tools for analyzing large datasets quickly and accurately, enabling businesses to extract valuable insights from their data. It supports both structured and semi-structured data, making it versatile for different types of data analysis, from simple queries to advanced analytics. Whether it’s running complex aggregations or time-series analyses, BigQuery’s scalability ensures consistent performance across a range of tasks. New customers can use their $300 in free credits to explore its full suite of data analysis tools, helping them gain insights and make data-driven decisions faster. The platform also supports real-time analytics, allowing businesses to react to data changes as they happen.

BigQuery enables businesses to create and manage data clean rooms, secure environments for processing sensitive data while ensuring privacy compliance. These clean rooms allow organizations to collaborate and analyze data without risking exposure of private or proprietary information. By maintaining strict access controls and ensuring data privacy, BigQuery fosters a secure environment for data analytics. New customers can experiment with BigQuery’s data clean room capabilities, utilizing the $300 in free credits to see firsthand how this secure, privacy-focused approach can meet their needs for compliant data analysis. This functionality is crucial for industries with stringent data privacy regulations, such as healthcare and finance.

BigQuery is an essential tool for data engineers, allowing them to streamline the process of data ingestion, transformation, and analysis. With its scalable infrastructure and robust suite of data engineering features, users can efficiently build data pipelines and automate workflows. BigQuery integrates easily with other Google Cloud tools, making it a versatile solution for data engineering tasks. New customers can take advantage of $300 in free credits to explore BigQuery’s features, enabling them to build and refine their data workflows for maximum efficiency and effectiveness. This allows engineers to focus more on innovation and less on managing the underlying infrastructure.

BigQuery provides a comprehensive suite of data preparation tools that help organizations clean, transform, and structure their data for analysis. With built-in SQL functions and compatibility with various ETL tools, BigQuery makes it easy to manipulate raw data and prepare it for complex queries. The platform also supports data partitioning and clustering, enhancing query performance during the data preparation phase. By automating many of the repetitive tasks, BigQuery helps streamline the data prep process, allowing teams to spend more time on analysis. New users can leverage the $300 in free credits to explore BigQuery’s data preparation tools and improve their data readiness for analytics.

BigQuery facilitates data science workflows by enabling data scientists to query, analyze, and model large datasets efficiently. The integration with Google Cloud’s machine learning tools allows for easy training and deployment of models directly within BigQuery. Data scientists can build predictive models using SQL and advanced analytics, empowering teams to make data-driven decisions. New customers get $300 in free credits to explore BigQuery’s data science capabilities, helping them accelerate their work and derive actionable insights from large datasets. This integration also enables seamless collaboration between data scientists and other business teams, improving overall productivity.

As a fully managed data warehouse solution, BigQuery allows businesses to store and analyze large volumes of data in a secure, scalable environment. Its serverless architecture eliminates the need for infrastructure management, enabling users to focus on data analysis instead of system maintenance. BigQuery’s highly efficient query engine ensures fast performance even with massive datasets, making it ideal for organizations of all sizes. New customers receive $300 in free credits, giving them the opportunity to test BigQuery’s features and determine how it can support their data storage and analytics needs. The platform’s ability to scale effortlessly makes it particularly well-suited for dynamic, high-growth organizations.

BigQuery is a powerful and flexible database that can handle both structured and semi-structured data at scale, making it suitable for a wide variety of use cases. It supports standard SQL for querying, enabling easy integration with existing workflows and tools. Its fully managed nature removes the complexity of database maintenance, allowing businesses to focus on deriving insights rather than managing infrastructure. New users can access $300 in free credits to test BigQuery’s capabilities, experimenting with both operational and analytical queries to see how it meets their needs for data storage and retrieval. With its robust security features, BigQuery also ensures that sensitive data remains protected, even at scale.

BigQuery offers a Database as a Service (DBaaS) model, providing fully managed data storage, query execution, and infrastructure without the need for users to manage servers or hardware. This serverless platform is designed for scalability, ensuring that businesses can handle large datasets without worrying about capacity or performance issues. BigQuery’s flexibility and ease of use make it an excellent choice for organizations seeking a DBaaS solution. New customers receive $300 in free credits, allowing them to explore BigQuery's features and experience its DBaaS capabilities without upfront costs. This approach eliminates database administration overhead, making it ideal for teams looking to focus on data analysis rather than maintenance.

ETL

BigQuery is an ideal tool for Extract, Transform, Load (ETL) processes, enabling businesses to automate data ingestion, transformation, and loading for analytics. It allows users to transform raw data into useful formats using SQL queries and integrates with various ETL tools to streamline workflows. The platform’s scalability ensures that ETL jobs run smoothly, even with vast amounts of data. New users can take advantage of the $300 in free credits to explore BigQuery’s ETL capabilities and experience the seamless processing of data for analytics. With its high-performance query engine, BigQuery ensures that ETL processes are fast and efficient, regardless of data size.

BigQuery offers machine learning capabilities through BigQuery ML, allowing users to build, train, and deploy machine learning models directly within the platform. This makes it easier for organizations to implement machine learning without needing to switch between multiple tools or environments. BigQuery ML integrates seamlessly with SQL, enabling data analysts and data scientists to work with machine learning models using familiar tools. New customers can use their $300 in free credits to experiment with BigQuery’s machine learning features, helping them unlock the potential of AI for predictive analytics and decision-making. The platform also supports various machine learning algorithms, making it a versatile tool for different use cases.

BigQuery is a powerful platform for marketing analytics, enabling businesses to analyze customer behavior, campaign performance, and market trends in real time. Its ability to process vast amounts of data quickly and its integration with other marketing tools makes it an invaluable resource for marketers looking to optimize their strategies. With BigQuery, marketers can leverage data to gain deeper insights into customer preferences and market dynamics. New customers can use $300 in free credits to explore BigQuery’s marketing analytics features, helping them make data-driven decisions that improve the effectiveness of their campaigns. The platform also supports real-time data analysis, enabling instant insights into ongoing marketing efforts.

BigQuery is optimized for Online Analytical Processing (OLAP), offering high-speed data queries and analysis on multidimensional datasets. It provides businesses with the ability to perform complex analytical queries on large datasets, supporting deep analysis across various business dimensions. The platform’s ability to scale automatically ensures that even large OLAP workloads are handled efficiently. New users can take advantage of $300 in free credits to explore how BigQuery can handle OLAP tasks, improving the speed and accuracy of their business intelligence processes. Its serverless architecture means businesses can focus on their data rather than managing infrastructure.

BigQuery functions as a Platform as a Service (PaaS), providing a fully managed environment for running SQL queries on massive datasets without the need for server management or infrastructure configuration. This makes it easier for businesses to scale their data analysis capabilities without investing in hardware or maintenance resources. BigQuery’s serverless model ensures that users can focus solely on analytics rather than worrying about underlying infrastructure. New customers can explore BigQuery’s PaaS features with $300 in free credits, allowing them to experience the benefits of serverless computing and high-performance data analysis. The platform's ability to scale with the demands of the business makes it an ideal choice for dynamic environments.

BigQuery is a powerful tool for predictive analytics, enabling businesses to leverage historical data to forecast future trends and behaviors. By integrating with machine learning tools like BigQuery ML, users can build and deploy predictive models directly within the platform. BigQuery’s performance and scalability make it easy to analyze large datasets quickly, helping businesses generate actionable insights for decision-making. New users can take advantage of $300 in free credits to explore BigQuery’s predictive analytics capabilities and build custom models that provide valuable forecasts. This functionality is essential for organizations seeking to improve their strategic planning and gain a competitive edge.

BigQuery features a highly optimized query engine that can handle large-scale queries on vast datasets with remarkable speed and efficiency. Its serverless architecture allows businesses to perform high-performance queries without the need for managing infrastructure or servers. BigQuery’s SQL-based query engine is familiar to most data analysts, making it easy to get started with complex data analysis. New customers can explore the query engine with $300 in free credits, enabling them to run a variety of queries and assess how BigQuery can support their analytical needs. The platform is also designed for scalability, ensuring that query performance remains consistent even as data grows.

BigQuery supports a wide variety of data formats, including XML, making it suitable for organizations working with XML data in addition to other structured and semi-structured data types. The platform’s flexibility allows users to load, query, and process XML data efficiently, enabling businesses to integrate XML with other data formats for comprehensive analysis. BigQuery’s powerful query engine ensures that XML data can be processed quickly, even when working with large volumes. New customers can explore BigQuery’s XML capabilities with $300 in free credits, helping them test how the platform handles XML alongside other formats. This capability makes BigQuery a versatile tool for diverse data processing needs.

Categories

Big Data Features

Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates

Business Intelligence Features

Ad Hoc Reports
Benchmarking
Budgeting & Forecasting
Dashboard
Data Analysis
Key Performance Indicators
Natural Language Generation (NLG)
Performance Metrics
Predictive Analytics
Profitability Analysis
Strategic Planning
Trend / Problem Indicators
Visual Analytics

Data Analysis Features

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

Data Management Features

Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge

Data Preparation Features

Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface

Data Science Features

Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports

Data Warehouse Features

Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge

ETL Features

Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control

Database Features

Backup and Recovery
Creation / Development
Data Migration
Data Replication
Data Search
Data Security
Database Conversion
Mobile Access
Monitoring
NOSQL
Performance Analysis
Queries
Relational Interface
Virtualization

Machine Learning Features

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Marketing Analytics Features

A/B Testing
Campaign Management
Channel Attribution
Customer Journey Mapping
Dashboard
Performance Metrics
Predictive Analytics
ROI Tracking
Social Media Metrics
Website Analytics

Predictive Analytics Features

AI / Machine Learning
Benchmarking
Data Blending
Data Mining
Demand Forecasting
For Education
For Healthcare
Modeling & Simulation
Sentiment Analysis

Big Data Features

Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates

Business Intelligence Features

Ad Hoc Reports
Benchmarking
Budgeting & Forecasting
Dashboard
Data Analysis
Key Performance Indicators
Natural Language Generation (NLG)
Performance Metrics
Predictive Analytics
Profitability Analysis
Strategic Planning
Trend / Problem Indicators
Visual Analytics

Data Management Features

Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge

Dashboard Features

Annotations
Data Source Integrations
Functions / Calculations
Interactive
KPIs
OLAP
Private Dashboards
Public Dashboards
Scorecards
Themes
Visual Analytics
Widgets

Data Fabric Features

Data Access Management
Data Analytics
Data Collaboration
Data Lineage Tools
Data Networking / Connecting
Metadata Functionality
No Data Redundancy
Persistent Data Management

Data Visualization Features

Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery

Embedded Analytics Features

Ad hoc Query
Application Development
Benchmarking
Dashboard
Interactive Reports
Mobile Reporting
Multi-User Collaboration
Self Service Analytics
Streaming Analytics
Visual Workflow Management

Reporting Features

Customizable Dashboard
Data Source Connectors
Drag & Drop
Drill Down
Email Reports
Financial Reports
Forecasting
Marketing Reports
OLAP
Report Export
Sales Reports
Scheduled / Automated Reports

Statistical Analysis Features

Analytics
Association Discovery
Compliance Tracking
File Management
File Storage
Forecasting
Multivariate Analysis
Regression Analysis
Statistical Process Control
Statistical Simulation
Survival Analysis
Time Series
Visualization

iPaaS Features

AI / Machine Learning
Cloud Data Integration
Dashboard
Data Quality Control
Data Security
Drag & Drop
Embedded iPaaS
Integration Management
Pre-Built Connectors
White Label
Workflow Management

Integrations

Blotout
Causal
DataHawk
Fullcast
Integrate.io
Kleene
Kraken
Microsoft Viva Goals
New Relic
OpenMetadata
Openbridge
Pendo
Pendula
Quickwork
Stackreaction
THRIVE
Timbr.ai
Workers by Delos
YepCode
data.world

Integrations

Blotout
Causal
DataHawk
Fullcast
Integrate.io
Kleene
Kraken
Microsoft Viva Goals
New Relic
OpenMetadata
Openbridge
Pendo
Pendula
Quickwork
Stackreaction
THRIVE
Timbr.ai
Workers by Delos
YepCode
data.world
Claim Domo and update features and information
Claim Domo and update features and information