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GLAIR uses 11 technologies like Apache, Apache Airflow, and Apache Kafka. View GLAIR's complete Tech Stack.

GLAIR Programming Languages And Frameworks Technology

The Apache Project is an effort to develop and maintain an open-source HTTP server for modern operating systems including UNIX and Windows. The goal of this project is to provide a secure, efficient and extensible server that provides HTTP services in sync with the current HTTP standards.
Apache Kafka is an open-source message broker project developed by the Apache Software Foundation written in Scala.
Python is an interpreted high-level programming language for general-purpose programming. Python features a dynamic type system and automatic memory management. It supports multiple programming paradigms, including object-oriented, imperative, functional and procedural, and has a large and comprehensive standard library.

GLAIR Productivity And Operations Technology

Apache Airflow is an open source workflow management platform that enables to programmatically author, schedule, and monitor workflows.

GLAIR Business Intelligence And Analytics Technology

Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
Apache Spark MLlib is an open source, scalable machine learning library, with APIs in Java, Scala, Python, and R.
MLflow is an open source platform which helps in managing complete Machine Learning lifecycle.
Tensorflow is an end-to-end open source machine learning platform. It allows developers to create large-scale neural networks with many layers.

GLAIR Platform And Storage Technology

Google Cloud Platform is a suite of cloud computing services that enables developers to build, deploy, and scale applications, websites, and services on the same infrastructure as Google.

GLAIR Devops And Development Technology

Google Kubernetes Engine is a powerful cluster manager and orchestration system for running your Docker containers. Set up a cluster in minutes.
Kubernetes helps to manage a cluster of Linux containers as a single system to accelerate development and simplify operations.

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