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What is Querri?

Querri stands out as a cutting-edge data analytics platform driven by artificial intelligence, designed to enhance data collaboration by enabling users to connect, clean, analyze, and visualize their data effortlessly within a single cohesive environment. Its user-friendly natural-language interface allows individuals to ask questions in simple English and receive instant visual feedback. The platform is equipped with automated data cleansing and ingestion tools that adeptly handle a variety of disorganized file formats, including CSV, Excel, JSON, and Parquet, as well as popular cloud storage services like Google Drive, OneDrive, and Dropbox, ensuring users can initiate their analyses without delay. Furthermore, a straightforward drag-and-drop dashboard builder promotes the quick creation of shareable reports, while compatibility with numerous spreadsheets and business applications, such as Excel, Smartsheet, QuickBooks, and Airtable, further amplifies its utility. Querri also offers white-label solutions that allow users to embed or modify the analytics engine within their own offerings, providing a customized experience for their clientele. This adaptability makes Querri an indispensable asset for organizations eager to utilize data efficiently and strategically. As businesses continue to seek innovative ways to harness their data, platforms like Querri will play a crucial role in shaping the future of data analytics.

What is Apache Parquet?

Parquet was created to offer the advantages of efficient and compressed columnar data formats across all initiatives within the Hadoop ecosystem. It takes into account complex nested data structures and utilizes the record shredding and assembly method described in the Dremel paper, which we consider to be a superior approach compared to just flattening nested namespaces. This format is specifically designed for maximum compression and encoding efficiency, with numerous projects demonstrating the substantial performance gains that can result from the effective use of these strategies. Parquet allows users to specify compression methods at the individual column level and is built to accommodate new encoding technologies as they arise and become accessible. Additionally, Parquet is crafted for widespread applicability, welcoming a broad spectrum of data processing frameworks within the Hadoop ecosystem without showing bias toward any particular one. By fostering interoperability and versatility, Parquet seeks to enable all users to fully harness its capabilities, enhancing their data processing tasks in various contexts. Ultimately, this commitment to inclusivity ensures that Parquet remains a valuable asset for a multitude of data-centric applications.

Media

Media

Integrations Supported

Airtable
JSON

Integrations Supported

APERIO DataWise
Amazon SageMaker Data Wrangler
Apache DataFusion
Blotout
Ficstar
Gable
GribStream
IBM Db2 Event Store
OpenObserve
OrcaSheets
QStudio
Semarchy xDI
StarfishETL
Streamkap
Tenzir
Tonic Ephemeral
Warp 10
e6data

API Availability

API Availability

Pricing Information

$16 per month
Free Version
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

Windows
Mac
Linux

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub
Webinars

Company Facts

Organization Name

Querri

Date Founded

2023

Company Location

United States

Company Website

querri.com

Company Facts

Organization Name

The Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

parquet.apache.org

Categories and Features

AI Data Analytics

Not specified

Categories and Features

Columnar Databases

Not specified

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