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ease
features
design
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 No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Actian Data Observability Yes 
Apache Flink Yes 
Apache Hive Yes 
Apache Spark Yes 
CelerData Cloud Yes 
Onehouse Yes 
PuppyGraph Yes 
Alluxio Yes 
Amazon Data Firehose No 
Amazon Redshift Yes 
Apache Cassandra Yes 
Apache Kafka Yes 
Azure Data Lake Yes 
Dremio No 
Google Cloud Lakehouse No 
Hadoop Yes 
MySQL Yes 
R2 SQL No 
SQL No 
e6data Yes 

Integrations

Actian Data Observability Yes 
Apache Flink Yes 
Apache Hive Yes 
Apache Spark Yes 
CelerData Cloud Yes 
Onehouse Yes 
PuppyGraph Yes 
Alluxio No 
Amazon Data Firehose Yes 
Amazon Redshift No 
Apache Cassandra No 
Apache Kafka No 
Azure Data Lake No 
Dremio Yes 
Google Cloud Lakehouse Yes 
Hadoop No 
MySQL No 
R2 SQL Yes 
SQL Yes 
e6data No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

Free
Open source
Free Trial No 
Free Version Yes 

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 Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
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 No 
Live Training (Online) No 
In Person No 

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 No 
Analytics No 
Data Integration No 
Data Migration No 
Data Quality Control No 
ETL - Extract / Transfer / Load No 
In-Memory Processing No 
Match & Merge No 

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 

Alternatives

Alternatives

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