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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 Iceberg?

Iceberg is an advanced format tailored for high-performance large-scale analytics, merging the user-friendly nature of SQL tables with the robust demands of big data. It allows multiple engines, including Spark, Trino, Flink, Presto, Hive, and Impala, to access the same tables seamlessly, enhancing collaboration and efficiency. Users can execute a variety of SQL commands to incorporate new data, alter existing records, and perform selective deletions. Moreover, Iceberg has the capability to proactively optimize data files to boost read performance, or it can leverage delete deltas for faster updates. By expertly managing the often intricate and error-prone generation of partition values within tables, Iceberg minimizes unnecessary partitions and files, simplifying the query process. This optimization leads to a reduction in additional filtering, resulting in swifter query responses, while the table structure can be adjusted in real time to accommodate evolving data and query needs, ensuring peak performance and adaptability. Additionally, Iceberg’s architecture encourages effective data management practices that are responsive to shifting workloads, underscoring its significance for data engineers and analysts in a rapidly changing environment. This makes Iceberg not just a tool, but a critical asset in modern data processing strategies.

Media

Media

Integrations Supported

CelerData Cloud
Onehouse
OpenMetadata
Presto
SQL
Stackable
StarRocks
Archon Data Store
Azure Marketplace
Cassandra
Databricks
Hadoop
NoSQL
Superset
Tableau
Timbr.ai

Integrations Supported

CelerData Cloud
Onehouse
OpenMetadata
Presto
SQL
Stackable
StarRocks
Apache Spark
Impala
Streamkap

API Availability

API Availability

Pricing Information

Free
Open source
Free Version

Pricing Information

Free
Open source
Free Version

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

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

iceberg.apache.org

Categories and Features

Big Data

Not specified

Database

Not specified

OLAP Databases

Not specified

Query Engines

Not specified

Categories and Features

Big Data

Not specified

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