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What is DuckDB?

Managing and storing tabular data, like that in CSV or Parquet formats, is crucial for effective data management practices. It's often necessary to transfer large sets of results to clients, particularly in expansive client-server architectures tailored for centralized enterprise data warehousing solutions. The task of writing to a single database while accommodating multiple concurrent processes also introduces various challenges that need to be addressed. DuckDB functions as a relational database management system (RDBMS), designed specifically to manage data structured in relational formats. In this setup, a relation is understood as a table, which is defined by a named collection of rows. Each row within a table is organized with a consistent set of named columns, where each column is assigned a particular data type to ensure uniformity. Moreover, tables are systematically categorized within schemas, and an entire database consists of a series of these schemas, allowing for structured interaction with the stored data. This organized framework not only bolsters the integrity of the data but also streamlines the process of querying and reporting across various datasets, ultimately improving data accessibility for users and applications alike.

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

Flyte
PuppyGraph
QStudio
Streamkap
Tad
APERIO DataWise
AnalyticsCreator
Apache DataFusion
Autymate
Blotout
CSViewer
Gable
Gravity Data
Hadoop
LanceDB
SDF
SQL
Tenzir
Timbr.ai
Warp 10

Integrations Supported

Flyte
PuppyGraph
QStudio
Streamkap
Tad
APERIO DataWise
AnalyticsCreator
Apache DataFusion
Autymate
Blotout
CSViewer
Gable
Gravity Data
Hadoop
LanceDB
SDF
SQL
Tenzir
Timbr.ai
Warp 10

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

DuckDB

Company Website

duckdb.org

Company Facts

Organization Name

The Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

parquet.apache.org

Categories and Features

Database

Backup and Recovery
Creation / Development
Data Migration
Data Replication
Data Search
Data Security
Database Conversion
Mobile Access
Monitoring
NOSQL
Performance Analysis
Queries
Relational Interface
Virtualization

Categories and Features

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