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What is CSViewer?

CSViewer is a fast and free desktop application designed for Windows users, enabling them to view and analyze large delimited text and binary files, including popular formats like CSV, TSV, Parquet, and QVD. It can quickly load millions of rows within seconds and offers advanced filtering capabilities as well as immediate profiling features, which cover aggregate functions, null counts, and outlier detection. Users can effortlessly export their filtered datasets, save their analysis setups, and generate visual representations through charts and cross-tabulations. Prioritizing exploratory data analysis without dependence on cloud services, CSViewer ensures that all aggregates and visual elements are updated in real-time whenever filters are adjusted or changed. Statistics for each column, such as null counts, unique values, and minimum or maximum values, are readily available for users to examine. Furthermore, users can export their selected rows into a new file for sharing or further analysis in different applications. The software also accommodates file conversion between various formats, allowing users to change CSV files into QVD format seamlessly. When opting to export to the native .dset format, users' data, along with any filters and visualizations applied, is preserved, making it easy to revisit their work later. This methodical approach not only simplifies data management but also significantly enhances the overall user experience while providing a robust tool for data analysis. Users can take full advantage of CSViewer’s capabilities to streamline their workflow efficiently.

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

Apache Parquet
EasyMorph
Microsoft Excel

Integrations Supported

Amazon Data Firehose
Autymate
CSViewer
Gravity Data
GribStream
Hadoop
Mage Sensitive Data Discovery
Meltano
OpenObserve
OrcaSheets
PuppyGraph
QStudio
SAS Studio
Semarchy xDI
Streamkap
Tenzir
Warp 10

API Availability

API Availability

Pricing Information

Free
Free Version

Pricing Information

Pricing not provided

Supported Platforms

Windows

Supported Platforms

Windows
Mac
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Webinars

Company Facts

Organization Name

EasyMorph

Date Founded

2014

Company Location

Canada

Company Website

csviewer.com

Company Facts

Organization Name

The Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

parquet.apache.org

Categories and Features

CSV Editors

Not specified

Categories and Features

Columnar Databases

Not specified

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