Displaying 1 to 5 from 5 results

Trino - A query engine that runs at ludicrous speed

  •    Java

Trino is a highly parallel and distributed query engine, that is built from the ground up for efficient, low latency analytics. It is an ANSI SQL compliant query engine, that works with BI tools such as R, Tableau, Power BI, Superset and many others. It helps to natively query data in Hadoop, S3, Cassandra, MySQL, and many others, without the need for complex, slow, and error-prone processes for copying the data.

mlops-kubernetes - GitOps state of MLOps Kubernetes cluster

  •    HCL

This repository contains the state of MLOps Kubernetes cluster managed with GitOps paradigm. A Kubernetes cluster >=1.21 with complete access via kubectl is needed to start. Runtime should be 'containerd'. Cluster should also have at least one node with an NVIDIA gpu.

trino - Trino: Master your translations with command line!

  •    Javascript

Trino CLI allows a quick and easy translation of words and phrases entered in the command line. Trino supports powerful, robust tabbed autocompletion by default, along with custom autocompletion on both commands and options.

trino-dbt-demo - Trino dbt demo project to mix and load BigQuery data with and in a local PostgreSQL database

  •    

dbt (data build tool) enables analytics engineers to transform data in their warehouses by simply writing SQL select statements. dbt handles turning these SQL select statements into tables and views (more details). Trino, formerly PrestoSQL, is a fast distributed SQL query engine for big data analytics that helps you explore your data universe and mix multiple data sources (more details).




versatile-data-kit - Versatile Data Kit is a data engineering framework that enables Data Engineers to develop, troubleshoot, deploy, run, and manage data processing workloads

  •    Python

Versatile Data Kit is a data engineering framework that enables Data Engineers to develop, troubleshoot, deploy, run, and manage data processing workloads (referred to as "Data Jobs"). A "Data Job" enables Data Engineers to implement automated pull ingestion (E in ELT) and batch data transformation (T in ELT) into a database. Versatile Data Kit provides an abstraction layer that helps solve common data engineering problems. It can be called by the workflow engine with the goal of making data engineers more efficient (for example, it ensures data applications are packaged, versioned and deployed correctly, while dealing with credentials, retries, reconnects, etc.). Everything exposed by Versatile Data Kit provides built-in monitoring, troubleshooting, and smart notification capabilities. For example, tracking both code and data modifications and the relations between them enables engineers to troubleshoot more quickly and provides an easy revert to a stable version.






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