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ease
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Description

Apache Hive is a data warehouse solution that enables the efficient reading, writing, and management of substantial datasets stored across distributed systems using SQL. It allows users to apply structure to pre-existing data in storage. To facilitate user access, it comes equipped with a command line interface and a JDBC driver. As an open-source initiative, Apache Hive is maintained by dedicated volunteers at the Apache Software Foundation. Initially part of the Apache® Hadoop® ecosystem, it has since evolved into an independent top-level project. We invite you to explore the project further and share your knowledge to enhance its development. Users typically implement traditional SQL queries through the MapReduce Java API, which can complicate the execution of SQL applications on distributed data. However, Hive simplifies this process by offering a SQL abstraction that allows for the integration of SQL-like queries, known as HiveQL, into the underlying Java framework, eliminating the need to delve into the complexities of the low-level Java API. This makes working with large datasets more accessible and efficient for developers.

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.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Apache Doris
Apache Spark
DataHub
e6data
AWS Marketplace
Activeeon ProActive
Amazon Redshift
Apache Avro
Apache Hudi
Apache Knox
Causal
Datalogz
DbVisualizer
IBM Cloud Mass Data Migration
Microsoft Power Query
SQLyog
Syntho
Tableau Catalog
Timbr.ai
WEBDEV

Integrations

Apache Doris
Apache Spark
DataHub
e6data
AWS Marketplace
Activeeon ProActive
Amazon Redshift
Apache Avro
Apache Hudi
Apache Knox
Causal
Datalogz
DbVisualizer
IBM Cloud Mass Data Migration
Microsoft Power Query
SQLyog
Syntho
Tableau Catalog
Timbr.ai
WEBDEV

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
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 Software Foundation

Founded

1999

Country

United States

Website

hive.apache.org

Vendor Details

Company Name

Apache Corporation

Founded

1954

Country

United States

Website

hudi.apache.org

Product Features

ETL

Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control

Product Features

Data Warehouse

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

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