Quaeris

Quaeris

Quaeris, Inc.
+
+
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

Align analytics to your everyday business workflows. Your business relies on people, data and documents, but the process of using them is broken. QuaerisAI enables seamless downstream workflows across your People, Documents and Data Assets. Use natural language search on data, documents and collaborate in private or within Communities - all in one platform! QuaerisAI offers time savings of at-least 30 minutes to an hour/day/resource - imagine the productivity enhancements you give your users without the expense of buying and consolidating a bunch of AI tools. Quaeris can be rolled out to team of 10s or 1000s of users seamlessly within a matter of days - without much need of IT, and that is why IT & data teams love us!

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Supported
Mac Supported
Linux Supported
Cloud Supported
On-Premises Supported
iPhone Supported
iPad Supported
Android Supported
Chromebook Supported

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

CROs, COOs, CIOs. Finance, Sales and Ops

Support

Phone Support Not Supported
24/7 Live Support Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Supported
Online Supported

API

Offers API Not Supported

API

Offers API Not Supported

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 Supported
Free Trial Supported

Pricing

$100 per month
Start with User Group based pricing or Consumption Based pricing.
Free Version Supported
Free Trial Supported

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 5.0 / 5
ease 4.3 / 5
features 4.3 / 5
design 5.0 / 5
support 5.0 / 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

  • QuaerisAI stands out as a converged enterprise search engine that finally bridges the gap between structured data and unstructured documents. No more toggling between platforms. No more copy-pasting SQL. I particularly appreciate the chat interface that lets you ask questions in plain English—ideal for non-technical users and a godsend for ops leaders trying to drive real-time insights. Features like BYOM (Bring Your Own Model) give flexibility that's rare. The Data Extract Agent is also a game-changer—transforming 1000s of docs into clean, structured spreadsheets instantly.
  • Quaeris is a sleek and lightweight platform and hence it is easier to implement. The visualizations and the dashboard features are excellent. Unlike other similar enterprise tools in the market, it doesn't require a lot of heavy lifting which makes it a great choice for faster implementation and enterprise-wide adoption.
  • Quaeris positions itself as a next-generation GenAI-powered analytics platform that transforms how businesses interact with data. Its core value proposition revolves around enabling self-service analytics through conversational queries, AI-driven insights, and embedded data storytelling. 1. Conversational Interface is Intuitive Quaeris allows business users (non-technical) to interact with complex datasets using simple natural language queries — similar to a ChatGPT-like interface for data analytics. 2. Speed to Insights Its ability to pull structured (databases) and unstructured (documents, reports) data into a unified query layer is a major time-saver for business intelligence (BI) workflows. 3. Embedded Analytics for SaaS Products Strong capability to integrate analytics and data visualizations natively into other SaaS applications — good for product teams. 4. Proactive Insights via AI Agents Rather than only responding to queries, Quaeris agents surface trends, anomalies, and business recommendations automatically. 5. Secure & Enterprise-Ready Focus on data governance, compliance, and secure deployment options (important for regulated industries like finance or healthcare). Key Features: Conversational Analytics (natural language queries to data) Embedded Analytics for SaaS platforms Enterprise Search across structured and unstructured data Data Stories — auto-generated visual narratives Proactive AI Agents that surface insights without being asked Collaboration features for data sharing and storytelling Secure, enterprise-grade decision intelligence

Cons

  • The learning curve to fully leverage all the advanced features—like pinboards and query inspection—might require more onboarding support or user training. The UI could benefit from more customization options for more technical users.
  • Haven't observed any significant limitations so far.
  • 1. Early Stage Product Maturity Quaeris is still evolving. Some users may find limitations in highly customized reporting or complex data modeling compared to mature BI platforms like Tableau or Power BI. 2. Data Preparation Still Required Although it enables natural language queries, the underlying data still needs to be structured, clean, and mapped correctly to get optimal results. 3. Enterprise Deployment Complexity Larger enterprises with diverse and siloed data systems may require significant integration effort for full value realization. 4. Graphic Instructions would Help the Novice As the product evolves, the onboarding of new customers can be improved by providing clear, visual instructions of its use. Step-by-step sequences and examples will be appreciated by the users.

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Supported
Live Online Supported
In Person Supported

Company Information

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

Company Information

Quaeris, Inc.
Founded: 2020
United States
www.quaeris.ai/

Alternatives

Alternatives

Looker

Looker

Google

Categories

AI Data Analytics Supported

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.

Big Data Supported

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.

Columnar Databases Supported

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.

Data Analysis Supported

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.

Data Clean Room Supported

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.

Data Engineering Supported

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.

Data Intelligence Supported
Data Management Supported
Data Preparation Supported

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.

Data Science Supported

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.

Data Warehouse Supported

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.

Database Supported

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 Supported

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.

Machine Learning Supported

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.

OLAP Databases Supported

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.

Query Engines Supported

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.

XML Databases Supported

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

Business Intelligence Features

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

Data Analysis Features

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

Marketing Analytics Features

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

Predictive Analytics Features

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

Big Data Features

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

Data Management Features

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

Data Preparation Features

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

Data Science Features

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

Data Warehouse Features

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

Database Features

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

ETL Features

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

Machine Learning Features

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

Business Intelligence Features

Ad Hoc Reports Supported
Benchmarking Not Supported
Budgeting & Forecasting Not Supported
Dashboard Supported
Data Analysis Supported
Key Performance Indicators Supported
Natural Language Generation (NLG) Supported
Performance Metrics Supported
Predictive Analytics Supported
Profitability Analysis Supported
Strategic Planning Not Supported
Trend / Problem Indicators Supported
Visual Analytics Supported

Data Analysis Features

Data Discovery Supported
Data Visualization Supported
High Volume Processing Supported
Predictive Analytics Supported
Regression Analysis Supported
Sentiment Analysis Not Supported
Statistical Modeling Not Supported
Text Analytics Not Supported

Marketing Analytics Features

A/B Testing Not Supported
Campaign Management Supported
Channel Attribution Supported
Customer Journey Mapping Not Supported
Dashboard Supported
Performance Metrics Supported
Predictive Analytics Not Supported
ROI Tracking Supported
Social Media Metrics Supported
Website Analytics Supported

Predictive Analytics Features

AI / Machine Learning Not Supported
Benchmarking Not Supported
Data Blending Not Supported
Data Mining Supported
Demand Forecasting Supported
For Education Supported
For Healthcare Supported
Modeling & Simulation Not Supported
Sentiment Analysis Not Supported

Dashboard Features

Annotations Supported
Data Source Integrations Supported
Functions / Calculations Supported
Interactive Supported
KPIs Supported
OLAP Not Supported
Private Dashboards Supported
Public Dashboards Supported
Scorecards Supported
Themes Not Supported
Visual Analytics Supported
Widgets Not Supported

Embedded Analytics Features

Ad hoc Query Supported
Application Development Not Supported
Benchmarking Not Supported
Dashboard Supported
Interactive Reports Supported
Mobile Reporting Supported
Multi-User Collaboration Supported
Self Service Analytics Supported
Streaming Analytics Supported
Visual Workflow Management Not Supported

HR Analytics Features

Compensation Plan Modeling Not Supported
Dashboard Supported
HR Metrics Library Supported
Leave & Absence Reporting Supported
Predictive Modeling Supported
Recruiting Management Not Supported
Succession Planning Not Supported
Talent Management Not Supported
Trend Analysis Supported
Turnover Tracking Supported

Natural Language Generation Features

Business Intelligence Supported
Chatbot Supported
CRM Data Analysis and Reports Supported
Email Marketing Not Supported
Financial Reporting Supported
Multiple Language Support Supported
SEO Not Supported
Web Content Not Supported

Natural Language Processing Features

Co-Reference Resolution Not Supported
In-Database Text Analytics Supported
Named Entity Recognition Supported
Natural Language Generation (NLG) Supported
Open Source Integrations Supported
Parsing Not Supported
Part-of-Speech Tagging Not Supported
Sentence Segmentation Not Supported
Stemming/Lemmatization Not Supported
Tokenization Not Supported

Product Analytics Features

Attribution Not Supported
Automatic Data Capture Supported
Churn Reporting Supported
Customer Feedback Collection Not Supported
Customer Guidance Supported
Customer Journey Analytics Not Supported
Data Export Supported
Data History Retention Supported
Data Labeling Not Supported
Product Engagement Scoring Not Supported
Real-Time Data Analysis Supported
Touchpoint Analytics Supported
User Segmentation Supported

Sales Analytics Features

Collaboration Tools Supported
Dashboards Supported
Forecasting Analytics Supported
Ideal Customer Profile (ICP) Not Supported
Lead Analytics Supported
Pipeline Management Supported
Predictive Forecasting Supported
Predictive Lead Scoring Not Supported
Sales Intelligence Reporting Supported

Integrations

Databricks Supported
dbt Supported
Agile Data Engine Supported
Azure Databricks Not Supported
Calendly Not Supported
ChartMogul Supported
Coginiti Supported
Control Plane Supported
DQOps Supported
ER/Studio Enterprise Edition Supported
FlashDocs Supported
Google Cloud Managed Service for Apache Airflow Supported
GrowthLoop Supported
Guru Not Supported
HubSpot CRM Not Supported
NetSpring Supported
Redpanda Agentic Data Plane Supported
Scispot Supported
Zendesk Guide Not Supported
qubesense Supported

Integrations

Databricks Supported
dbt Supported
Agile Data Engine Not Supported
Azure Databricks Supported
Calendly Supported
ChartMogul Not Supported
Coginiti Not Supported
Control Plane Not Supported
DQOps Not Supported
ER/Studio Enterprise Edition Not Supported
FlashDocs Not Supported
Google Cloud Managed Service for Apache Airflow Not Supported
GrowthLoop Not Supported
Guru Supported
HubSpot CRM Supported
NetSpring Not Supported
Redpanda Agentic Data Plane Not Supported
Scispot Not Supported
Zendesk Guide Supported
qubesense Not Supported
Claim Quaeris and update features and information
Claim Quaeris and update features and information