Trino
Trino: Lightning-fast SQL query engine for your data
Trino, formerly known as PrestoSQL, is a distributed SQL query engine that enables high-performance big data analytics. With Trino, users can quickly and efficiently access large volumes of data from various sources such as Hadoop, S3, Cassandra and relational databases. The SQL query engine executes queries from multiple data sources without major latencies. It is therefore ideally suited for data analysis and BI tasks.
The Trino highlights at a glance
High-performance queries
Fast query execution, which makes Trino ideal for big data analysis.
Federated Queries
Integration of data from different and heterogeneous data sources with just a single query
Simple integration
Is compatible with existing data warehouses and databases through connectors.
Flexible operation
Trino runs both on-premise and in cloud environments such as Amazon, Azure and Google Cloud
Versatile data format
Various data formats are supported, including JSON, ORC and Parquet.
Scalability
Petabyte-sized amounts of data can be processed effortlessly with Trino.
Christopher Keller
Director Big Data Analytics & IoT
Together we master your data integration challenges
it-novum Professional Services
Implementation
Implementation of Trino
PoC / PoV
Proof-of-concept / proof-of-value for your use case with Trino
Consulting
360° consulting for the implementation of your Trino project
Trainings and Workshops
KnowHow development with trainings and individual workshops
FAQ
Trino splits queries into fragments that are executed simultaneously on different nodes in the cluster.
This allows us to process large amounts of data quickly and efficiently by using distributed resources.
This parallel processing enables us to answer complex queries quickly.
To access the data processed in Trino, you connect to a Trino cluster via JDBC, ODBC or the REST API.
You then use an SQL client tool such as DBeaver to formulate and execute your queries.
The results are sent from the Trino cluster to your client tool and displayed there.
Although Trino does not have a Salesforce Connector, a connection to Salesforce can be established by extracting data from Salesforce using an ETL tool and saving it in a supported format.
This data can then be loaded into Trino and queried.
Starburst offers additional features and integrations that can facilitate this process.
When working with Trino, it is advisable to use a GUI tool.
Although the CLI tools are practical, GUI tools such as DBeaver can improve usability and facilitate complex queries.
In short, yes, Trino offers a JDBC interface that allows you to connect to a Trino cluster via JDBC (Java Database Connectivity).
Tableau works well with Trino.
The Tableau Connector/JDBC is a popular option to integrate Tableau with various data sources, including Trino.
Analyzing data stored in Amazon S3 works very well with Trino.
Trino offers native support for connecting to S3 and is designed to process large amounts of data efficiently.
You can use the JDBC interface or the ODBC driver from Trino to establish a connection.
Alternatively, you can use the REST API.
Some BI applications also offer native integrations with Trino.
However, JDBC or ODBC are usually the preferred options for connecting BI applications to Trino.
In Trino, external tables are used to access data, such as in files or another system.
For nested JSON data, you set up external tables by defining the data structure to interpret the JSON file correctly.
Trino can then use these tables to access the JSON data and execute queries as if they were stored in a traditional database table.
With Trino, you can access various data sources that may not be directly supported by Pentaho or that you don’t want to connect via ETL, which expands your analytics capabilities.
In addition, Trino provides a data governance layer that improves the control and management of your data while simplifying ETL processes by enabling fast and efficient processing of large amounts of data.
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