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Description

Iceberg is an advanced format designed for managing extensive analytical tables efficiently. It combines the dependability and ease of SQL tables with the capabilities required for big data, enabling multiple engines such as Spark, Trino, Flink, Presto, Hive, and Impala to access and manipulate the same tables concurrently without issues. The format allows for versatile SQL operations to incorporate new data, modify existing records, and execute precise deletions. Additionally, Iceberg can optimize read performance by eagerly rewriting data files or utilize delete deltas to facilitate quicker updates. It also streamlines the complex and often error-prone process of generating partition values for table rows while automatically bypassing unnecessary partitions and files. Fast queries do not require extra filtering, and the structure of the table can be adjusted dynamically as data and query patterns evolve, ensuring efficiency and adaptability in data management. This adaptability makes Iceberg an essential tool in modern data workflows.

Description

Parquet was developed to provide the benefits of efficient, compressed columnar data representation to all projects within the Hadoop ecosystem. Designed with a focus on accommodating complex nested data structures, Parquet employs the record shredding and assembly technique outlined in the Dremel paper, which we consider to be a more effective strategy than merely flattening nested namespaces. This format supports highly efficient compression and encoding methods, and various projects have shown the significant performance improvements that arise from utilizing appropriate compression and encoding strategies for their datasets. Furthermore, Parquet enables the specification of compression schemes at the column level, ensuring its adaptability for future developments in encoding technologies. It is crafted to be accessible for any user, as the Hadoop ecosystem comprises a diverse range of data processing frameworks, and we aim to remain neutral in our support for these different initiatives. Ultimately, our goal is to empower users with a flexible and robust tool that enhances their data management capabilities across various applications.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Amazon Data Firehose Yes 
PuppyGraph Yes 
Streamkap Yes 
3LC No 
APERIO DataWise No 
Amazon SageMaker Data Wrangler No 
Autymate No 
CSViewer No 
Daft Yes 
Data Sentinel No 
Dell AI-Ready Data Platform Yes 
Flyte No 
Impala Yes 
Mage Sensitive Data Discovery No 
Presto Yes 
QuerySurge No 
SSIS Integration Toolkit No 
Tictable No 
Timeplus No 
Trino Yes 

Integrations

Amazon Data Firehose Yes 
PuppyGraph Yes 
Streamkap Yes 
3LC Yes 
APERIO DataWise Yes 
Amazon SageMaker Data Wrangler Yes 
Autymate Yes 
CSViewer Yes 
Daft No 
Data Sentinel Yes 
Dell AI-Ready Data Platform No 
Flyte Yes 
Impala No 
Mage Sensitive Data Discovery Yes 
Presto No 
QuerySurge Yes 
SSIS Integration Toolkit Yes 
Tictable Yes 
Timeplus Yes 
Trino No 

Pricing Details

Free
Open source
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Apache Software Foundation

Founded

1999

Country

United States

Website

iceberg.apache.org

Vendor Details

Company Name

The Apache Software Foundation

Founded

1999

Country

United States

Website

parquet.apache.org

Product Features

Big Data

Collaboration No 
Data Blends No 
Data Cleansing No 
Data Mining No 
Data Visualization No 
Data Warehousing No 
High Volume Processing No 
No-Code Sandbox No 
Predictive Analytics No 
Templates No 

Product Features

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