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What is Rons Data Stream?

Rons Data Stream is a versatile Windows application that efficiently cleans or updates numerous data sources in mere seconds, regardless of file size, through the use of its specialized tools known as Cleaners. These "Cleaners" comprise a collection of operations derived from an extensive array of processing rules for Columns, Rows, and Cells, which can be created, saved, and applied across various data sources, allowing for their reuse in multiple Jobs. The application features a Preview window that displays both the original dataset and a processed version, ensuring the results of each rule are presented in a clear and comprehensible manner. Jobs encompass all necessary information for batch processing, enabling users to tackle hundreds of files simultaneously, which simplifies the task of cleaning an entire directory. Additionally, Rons Data Stream supports conversion between SQL, Parquet, and various tabular formats including CSV and HTML, as well as XML files, making it a highly adaptable tool. It can function independently or enhance the capabilities of Rons Data Editor, further empowering CSV Editors and Data Processing applications for users seeking efficient data management solutions.

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

3LC
APERIO DataWise
Amazon SageMaker Data Wrangler
Arroyo
Autymate
Blotout
Flyte
Gable
Gravity Data
Hadoop
Indexima Data Hub
Mage Sensitive Data Discovery
PuppyGraph
QStudio
SDF
StarfishETL
Timbr.ai
Timeplus
Tonic Ephemeral
Warp 10

Integrations Supported

3LC
APERIO DataWise
Amazon SageMaker Data Wrangler
Arroyo
Autymate
Blotout
Flyte
Gable
Gravity Data
Hadoop
Indexima Data Hub
Mage Sensitive Data Discovery
PuppyGraph
QStudio
SDF
StarfishETL
Timbr.ai
Timeplus
Tonic Ephemeral
Warp 10

API Availability

Has API

API Availability

Has API

Pricing Information

$35
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Rons Place Software

Date Founded

2013

Company Location

Canada

Company Website

www.ronsplace.ca/products/ronsdatastream

Company Facts

Organization Name

The Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

parquet.apache.org

Categories and Features

Categories and Features

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