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features
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support

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Description

Hudi serves as a robust platform for constructing streaming data lakes equipped with incremental data pipelines, all while utilizing a self-managing database layer that is finely tuned for lake engines and conventional batch processing. It effectively keeps a timeline of every action taken on the table at various moments, enabling immediate views of the data while also facilitating the efficient retrieval of records in the order they were received. Each Hudi instant is composed of several essential components, allowing for streamlined operations. The platform excels in performing efficient upserts by consistently linking a specific hoodie key to a corresponding file ID through an indexing system. This relationship between record key and file group or file ID remains constant once the initial version of a record is written to a file, ensuring stability in data management. Consequently, the designated file group encompasses all iterations of a collection of records, allowing for seamless data versioning and retrieval. This design enhances both the reliability and efficiency of data operations within the Hudi ecosystem.

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.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Apache Flink
Apache Hive
Apache Spark
Onehouse
PuppyGraph
AWS Marketplace
Alluxio
Amazon Data Firehose
Apache Impala
Apache Kafka
Azure Data Lake
Dell AI-Ready Data Platform
MySQL
PostgreSQL
Presto
SQL
Salesforce Data Cloud
Streamkap
Tabular
e6data

Integrations

Apache Flink
Apache Hive
Apache Spark
Onehouse
PuppyGraph
AWS Marketplace
Alluxio
Amazon Data Firehose
Apache Impala
Apache Kafka
Azure Data Lake
Dell AI-Ready Data Platform
MySQL
PostgreSQL
Presto
SQL
Salesforce Data Cloud
Streamkap
Tabular
e6data

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

Free
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Apache Corporation

Founded

1954

Country

United States

Website

hudi.apache.org

Vendor Details

Company Name

Apache Software Foundation

Founded

1999

Country

United States

Website

iceberg.apache.org

Product Features

Data Warehouse

Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge

Product Features

Big Data

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

Alternatives

Alternatives

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