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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.

What is Apache Kudu?

A Kudu cluster organizes its information into tables that are similar to those in conventional relational databases. These tables can vary from simple binary key-value pairs to complex designs that contain hundreds of unique, strongly-typed attributes. Each table possesses a primary key made up of one or more columns, which may consist of a single column like a unique user ID, or a composite key such as a tuple of (host, metric, timestamp), often found in machine time-series databases. The primary key allows for quick access, modification, or deletion of rows, which ensures efficient data management. Kudu's straightforward data model simplifies the process of migrating legacy systems or developing new applications without the need to encode data into binary formats or interpret complex databases filled with hard-to-read JSON. Moreover, the tables are self-describing, enabling users to utilize widely-used tools like SQL engines or Spark for data analysis tasks. The user-friendly APIs that Kudu offers further increase its accessibility for developers. Consequently, Kudu not only streamlines data management but also preserves a solid structural integrity, making it an attractive choice for various applications. This combination of features positions Kudu as a versatile solution for modern data handling challenges.

Media

Media

Integrations Supported

Hadoop
Amazon Data Firehose
Amazon SageMaker Data Wrangler
Apache DataFusion
Apache Spark
Arroyo
Autymate
BigBI
Data Sentinel
Flyte
Gable
Indexima Data Hub
MLJAR Studio
Mage Platform
SDF
Semarchy xDI
StarfishETL
Tad
Timeplus
Tonic Ephemeral

Integrations Supported

Hadoop
Amazon Data Firehose
Amazon SageMaker Data Wrangler
Apache DataFusion
Apache Spark
Arroyo
Autymate
BigBI
Data Sentinel
Flyte
Gable
Indexima Data Hub
MLJAR Studio
Mage Platform
SDF
Semarchy xDI
StarfishETL
Tad
Timeplus
Tonic Ephemeral

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
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

The Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

parquet.apache.org

Company Facts

Organization Name

The Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

kudu.apache.org/overview.html

Categories and Features

Categories and Features

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