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What is Trino?

Trino is an exceptionally swift query engine engineered for remarkable performance. This high-efficiency, distributed SQL query engine is specifically designed for big data analytics, allowing users to explore their extensive data landscapes. Built for peak efficiency, Trino shines in low-latency analytics and is widely adopted by some of the biggest companies worldwide to execute queries on exabyte-scale data lakes and massive data warehouses. It supports various use cases, such as interactive ad-hoc analytics, long-running batch queries that can extend for hours, and high-throughput applications that demand quick sub-second query responses. Complying with ANSI SQL standards, Trino is compatible with well-known business intelligence tools like R, Tableau, Power BI, and Superset. Additionally, it enables users to query data directly from diverse sources, including Hadoop, S3, Cassandra, and MySQL, thereby removing the burdensome, slow, and error-prone processes related to data copying. This feature allows users to efficiently access and analyze data from different systems within a single query. Consequently, Trino's flexibility and power position it as an invaluable tool in the current data-driven era, driving innovation and efficiency across industries.

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.

Media

Media

Integrations Supported

Apache Iceberg
Apache Phoenix
CelerData Cloud
Coginiti
DataClarity Unlimited Analytics
DataHub
DbVisualizer
Hue
SQL
SecuPi
Stackable
StarRocks
Timbr.ai
Mitzu

Integrations Supported

Apache Iceberg
Apache Phoenix
CelerData Cloud
Coginiti
DataClarity Unlimited Analytics
DataHub
DbVisualizer
Hue
SQL
SecuPi
Stackable
StarRocks
Timbr.ai
Acryl Data
Aqua Data Studio
Ascend
Fosfor Decision Cloud
Jotform

API Availability

API Availability

Pricing Information

Free
Open source
Free Version

Pricing Information

Pricing not provided

Supported Platforms

SaaS
Windows

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
On-Site Training

Company Facts

Organization Name

Trino

Company Website

trino.io

Company Facts

Organization Name

Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

hive.apache.org

Categories and Features

Big Data

Not specified

Database

Not specified

OLAP Databases

Not specified

Query Engines

Not specified

Categories and Features

ETL

Not specified

Query Engines

Not specified

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