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What is Databend?

Databend stands out as a pioneering, cloud-centric data warehouse designed for high-speed, cost-efficient analytics tailored for large-scale data processing requirements. Its flexible architecture enables it to adjust seamlessly to fluctuating workloads, thus optimizing resource utilization and minimizing costs. Built using Rust, Databend boasts impressive performance features like vectorized query execution and columnar storage, which significantly improve the speed of data retrieval and processing tasks. The cloud-first design allows for easy integration with a range of cloud services, while also emphasizing reliability, data consistency, and resilience against failures. As an open-source platform, Databend offers a flexible and user-friendly solution for data teams seeking efficient management of big data analytics in cloud settings. Furthermore, its ongoing updates and support from the community guarantee that users are equipped with the most current advancements in data processing technology, ensuring a competitive edge in the rapidly evolving data landscape. This commitment to innovation makes Databend a compelling choice for organizations aiming to harness the full potential of their data.

What is Apache Hudi?

Hudi is a versatile framework designed for the development of streaming data lakes, which seamlessly integrates incremental data pipelines within a self-managing database context, while also catering to lake engines and traditional batch processing methods. This platform maintains a detailed historical timeline that captures all operations performed on the table, allowing for real-time data views and efficient retrieval based on the sequence of arrival. Each Hudi instant is comprised of several critical components that bolster its capabilities. Hudi stands out in executing effective upserts by maintaining a direct link between a specific hoodie key and a file ID through a sophisticated indexing framework. This connection between the record key and the file group or file ID remains intact after the original version of a record is written, ensuring a stable reference point. Essentially, the associated file group contains all iterations of a set of records, enabling effortless management and access to data over its lifespan. This consistent mapping not only boosts performance but also streamlines the overall data management process, making it considerably more efficient. Consequently, Hudi's design provides users with the tools necessary for both immediate data access and long-term data integrity.

Media

Media

Integrations Supported

AWS Marketplace
Alluxio
Amazon Athena
Amazon Redshift
Amazon Web Services (AWS)
Apache Cassandra
Apache Doris
Apache Flink
Apache Hive
Apache Kafka
Apache Spark
Azure Data Lake
DataHub
Hadoop
MySQL
Onehouse
PostgreSQL
Presto
TapData
e6data

Integrations Supported

AWS Marketplace
Alluxio
Amazon Athena
Amazon Redshift
Amazon Web Services (AWS)
Apache Cassandra
Apache Doris
Apache Flink
Apache Hive
Apache Kafka
Apache Spark
Azure Data Lake
DataHub
Hadoop
MySQL
Onehouse
PostgreSQL
Presto
TapData
e6data

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Databend

Date Founded

2021

Company Location

Singapore

Company Website

databend.rs/

Company Facts

Organization Name

Apache Corporation

Date Founded

1954

Company Location

United States

Company Website

hudi.apache.org

Categories and Features

Data Warehouse

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

Database

Backup and Recovery
Creation / Development
Data Migration
Data Replication
Data Search
Data Security
Database Conversion
Mobile Access
Monitoring
NOSQL
Performance Analysis
Queries
Relational Interface
Virtualization

Categories and 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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