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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

VeloDB, which utilizes Apache Doris, represents a cutting-edge data warehouse designed for rapid analytics on large-scale real-time data. It features both push-based micro-batch and pull-based streaming data ingestion that occurs in mere seconds, alongside a storage engine capable of real-time upserts, appends, and pre-aggregations. The platform delivers exceptional performance for real-time data serving and allows for dynamic interactive ad-hoc queries. VeloDB accommodates not only structured data but also semi-structured formats, supporting both real-time analytics and batch processing capabilities. Moreover, it functions as a federated query engine, enabling seamless access to external data lakes and databases in addition to internal data. The system is designed for distribution, ensuring linear scalability. Users can deploy it on-premises or as a cloud service, allowing for adaptable resource allocation based on workload demands, whether through separation or integration of storage and compute resources. Leveraging the strengths of open-source Apache Doris, VeloDB supports the MySQL protocol and various functions, allowing for straightforward integration with a wide range of data tools, ensuring flexibility and compatibility across different environments.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Apache Doris
Apache Spark
Amazon EMR
Apache Hudi
Apache Iceberg
Astro by Astronomer
DBeaver Community
DataHub
Datalogz
DigDash
Fosfor Decision Cloud
Hue
Immuta
Omniscope Evo
Protegrity
Rational BI
Salesforce Data 360
StarRocks
TapData
WEBDEV

Integrations

Apache Doris
Apache Spark
Amazon EMR
Apache Hudi
Apache Iceberg
Astro by Astronomer
DBeaver Community
DataHub
Datalogz
DigDash
Fosfor Decision Cloud
Hue
Immuta
Omniscope Evo
Protegrity
Rational BI
Salesforce Data 360
StarRocks
TapData
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

VeloDB

Founded

2023

Country

Singapore

Website

www.velodb.io

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

Alternatives

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The Apache Software Foundation
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Apache Hudi

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