SAFMQ: Store and Forward Message Queue, message oriented middleware. Uses include Assured Async Messaging, SOA, Delayed/Batch, and Cluster/Grid Computing. The SAFMQ server provides cross platform communication among C++, PHP, Java, and .NET clients.
A community repository to develop Commodity Grid (CoG) Software for the access of Grids, through high level interfaces. The main repository is maintained at http://www.cogkit.org
Cluster101 allows you to run software on many hosts and perform a simple task scheduling. No need to install any software on the hosts (it just runs tasks via ssh). It is typically used for running scientific applications on University campuses.
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Creation of workflows that will be executed on clusters. Must be able to easily create task sequences (like Automator) and to exchange data with the cluster. Monitoring may be web-based.
Acelet-Scheduler with SuperScheduler and SuperWatchdog is a Java task scheduler with daemon and GUI for system and application job scheduling, can schedule tasks in a distributed environment. Holiday adjustable. Works out-box. See http://www.acelet.com
The Gridbus Grid Service Broker, is a service-oriented, economy and data-aware resource broker system that uses a simple, extensible middleware independent architecture that mediates access to distributed resources on a local / Global Grid of computers.
HyGrid provides a mechanism for building a grid of hybrid nature that could be used to handle the jobs requiring huge computational, storage or both the resources at the same time.
Cloud data warehouse to power your data-driven innovation
BigQuery is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data.
BigQuery Studio provides a single, unified interface for all data practitioners of various coding skills to simplify analytics workflows from data ingestion and preparation to data exploration and visualization to ML model creation and use. It also allows you to use simple SQL to access Vertex AI foundational models directly inside BigQuery for text processing tasks, such as sentiment analysis, entity extraction, and many more without having to deal with specialized models.