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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 HBase?

When you need immediate and random read/write capabilities for large datasets, Apache HBaseâ„¢ is a solid option to consider. This project specializes in handling enormous tables that can consist of billions of rows and millions of columns across clusters made of standard hardware. It includes automatic failover functionalities among RegionServers to guarantee continuous operation without interruptions. In addition, it features a straightforward Java API for client interaction, simplifying the process for developers. There is also a Thrift gateway and a RESTful Web service available, which supports a variety of data encoding formats, such as XML, Protobuf, and binary. Moreover, it allows for the export of metrics through the Hadoop metrics subsystem, which can integrate with files or Ganglia, or even utilize JMX for improved monitoring. This adaptability positions it as a robust solution for organizations with significant data management requirements, making it a preferred choice for those looking to optimize their data handling processes.

Media

Media

Integrations Supported

Data Sentinel
Mage Platform
Mage Sensitive Data Discovery
Amazon Data Firehose
Apache DataFusion
Ficstar
GribStream
MLJAR Studio
OpenObserve
PuppyGraph
Querri
QuerySurge
Tad
Timeplus
Tonic Ephemeral

Integrations Supported

Data Sentinel
Mage Platform
Mage Sensitive Data Discovery
Akira AI
Apache Ranger
Apache Spark
DigDash
Lyftrondata

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Free, Open Source Software

Supported Platforms

Windows
Mac
Linux

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Not specified

Training Options

Documentation Hub
Webinars

Training Options

Documentation Hub

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

hbase.apache.org

Categories and Features

Columnar Databases

Not specified

Categories and Features

Columnar Databases

Not specified

Distributed Databases

Not specified

Key-Value Databases

Not specified

NoSQL Database

Auto-sharding
Data Model Flexibility
Deployment Flexibility
Dynamic Schemas
Integrated Caching

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