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What is Apache Hive?

Apache Hive serves as a data warehousing framework that empowers users to access, manipulate, and oversee large datasets spread across distributed systems using a SQL-like language. It facilitates the structuring of pre-existing data stored in various formats. Users have the option to interact with Hive through a command line interface or a JDBC driver. As a project under the auspices of the Apache Software Foundation, Apache Hive is continually supported by a group of dedicated volunteers. Originally integrated into the Apache® Hadoop® ecosystem, it has matured into a fully-fledged top-level project with its own identity. We encourage individuals to delve deeper into the project and contribute their expertise. To perform SQL operations on distributed datasets, conventional SQL queries must be run through the MapReduce Java API. However, Hive streamlines this task by providing a SQL abstraction, allowing users to execute queries in the form of HiveQL, thus eliminating the need for low-level Java API implementations. This results in a much more user-friendly and efficient experience for those accustomed to SQL, leading to greater productivity when dealing with vast amounts of data. Moreover, the adaptability of Hive makes it a valuable tool for a diverse range of data processing tasks.

What is Apache Doris?

Apache Doris is a sophisticated data warehouse specifically designed for real-time analytics, allowing for remarkably quick access to large-scale real-time datasets. This system supports both push-based micro-batch and pull-based streaming data ingestion, processing information within seconds, while its storage engine facilitates real-time updates, appends, and pre-aggregations. Doris excels in managing high-concurrency and high-throughput queries, leveraging its columnar storage engine, MPP architecture, cost-based query optimizer, and vectorized execution engine for optimal performance. Additionally, it enables federated querying across various data lakes such as Hive, Iceberg, and Hudi, in addition to traditional databases like MySQL and PostgreSQL. The platform also supports intricate data types, including Array, Map, and JSON, and includes a variant data type that allows for the automatic inference of JSON data structures. Moreover, advanced indexing methods like NGram bloomfilter and inverted index are utilized to enhance its text search functionalities. With a distributed architecture, Doris provides linear scalability, incorporates workload isolation, and implements tiered storage for effective resource management. Beyond these features, it is engineered to accommodate both shared-nothing clusters and the separation of storage and compute resources, thereby offering a flexible solution for a wide range of analytical requirements. In conclusion, Apache Doris not only meets the demands of modern data analytics but also adapts to various environments, making it an invaluable asset for businesses striving for data-driven insights.

Media

Media

Integrations Supported

Apache Hudi
Apache Spark
TapData
Adobe Real-Time CDP
CelerData Cloud
DBeaver Community
IBM watsonx.data
LightBeam.ai
Mage Static Data Masking
Omniscope Evo
PHEMI Health DataLab
Predibase
Progress DataDirect
Secoda
WINDEV
lakeFS

Integrations Supported

Apache Hudi
Apache Spark
TapData
Apache Flink
Apache Hive
Baidu Palo

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Free
Open source
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Not specified

Training Options

Documentation Hub
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

hive.apache.org

Company Facts

Organization Name

The Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

doris.apache.org

Categories and Features

ETL

Not specified

Query Engines

Not specified

Categories and Features

Data Warehouse

Not specified

OLAP Databases

Not specified

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