Search Results for "dataflow"
Sort By:
Showing 18 open source projects for "dataflow"
View related business solutions-
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
-
Veeam Data Platform v13.1 - Get Your Free TrialTry Veeam Data Platform today. Experience the unified platform that's secure by design, portable by default, and proven to recover clean, fast, and anywhere.
-
1
Google Cloud Dataflow Template Pipelines
Cloud Dataflow Google-provided templates for solving data tasks
DataflowTemplates is the source repository for Google-provided Dataflow templates that are intended to solve large-scale in-cloud data processing tasks without requiring users to build everything from scratch in a full development environment. The repository is centered on templated pipelines powered by Google Cloud Dataflow and Apache Beam, making it easier to run common integration and movement jobs such as data import, export, backup, restore, and bulk API operations. ... -
2
WALA
Libraries for Analysis, with frontends for Java, Android, and JS
The T. J. Watson Libraries for Analysis (WALA) provide static analysis capabilities for Java bytecode and related languages and for JavaScript. The system is licensed under the Eclipse Public License, which has been approved by the OSI (Open Source Initiative) as a fully certified open-source license. The initial WALA infrastructure was independently developed as part of the DOMO research project at the IBM T.J. Watson Research Center. In 2006, IBM donated the software to the community. The... -
3
Apache Beam
Unified programming model for Batch and Streaming
...These pipelines are executed on one of Beam’s supported distributed processing back-ends, which include Apache Apex, Apache Flink, Apache Spark, and Google Cloud Dataflow. Beam is especially useful for Embarrassingly Parallel data processing tasks, and caters to the different needs and backgrounds of end users, SDK writers and runner writers. -
4
ElasticJob
Distributed scheduled job framework
ElasticJob is a distributed scheduling solution consisting of two separate projects, ElasticJob-Lite and ElasticJob-Cloud. ElasticJob-Lite is a lightweight, decentralized solution that provides distributed task sharding services. ElasticJob-Cloud uses Mesos to manage and isolate resources. It uses a unified job API for each project. Developers only need code one time and can deploy at will. Support job sharding and high availability in distributed system. Scale out for throughput and... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
5
Apache Flink
Stream processing framework with powerful stream
Apache Flink is a distributed engine for stateful computations over data streams and batches, designed for low-latency processing at scale. Its core runtime executes dataflow graphs with fine-grained backpressure and checkpointing, allowing applications to recover consistently from failures. Flink’s event-time model and watermarks enable accurate out-of-order processing, windowing, and complex time semantics that typical real-time systems struggle with. Developers program against high-level APIs—DataStream and Table/SQL—to express transformations, joins, and stateful patterns, while specialized libraries support CEP, machine learning workflows, and connectors. ... -
6
SwiftVis
Data Exploration for Swift and other N-body simulation
This is a project that was started back in 2001 to help data analysis for a revision of Hal Levison's Swift planetary simulation framework. SwiftVis is a data exploration and visualization package written in Java that has a GUI which supports the creation of visual "dataflow programs" and can be used by non-programmers. -
7
Easy Machine Learning
Easy Machine Learning is a general-purpose dataflow-based system
...The key barriers come from not only the implementation of the algorithms themselves but also the processing for applying them to real applications which often involve multiple steps and different algorithms. Our platform Easy Machine Learning presents a general-purpose dataflow-based system for easing the process of applying machine learning algorithms to real-world tasks. In the system, a learning task is formulated as a directed acyclic graph (DAG) in which each node represents an operation (e.g. a machine learning algorithm), and each edge represents the flow of the data from one node to its descendants. -
8
autoCode4
Synthesizing embedded control software from formal specifications
autoCode4 is an engine that synthesizes controllers from formal specifications described under a subset of linear temporal logic (LTL). Importantly, it synthesizes synchronous dataflow controllers (in Lustre or in Ptolemy II form) and maintains requirement-to-code traceability. Such feature is mandated in developing safety-critical systems and are considered essential for specification validation or integrating manual implementation such as legacy code. The LTL specification captures the desired behavior of a controller where the environment takes the first move (i.e., sense/input then react/output), so the synthesized controller can be viewed as a Mealy machine. ... -
9
ICon (Input Configurator) is a Java-based system for managing input devices and building advanced interaction techniques using a dataflow model. It contains a runtime engine, a rich library of input devices, several processing modules and a visual editor.
-
Save Up to 91% on Cloud Compute With Spot VMsRun batch jobs at 60-91% off with Spot VMs. Long-running workloads get automatic discounts with sustained use.
-
10
The Open RVC-CAL Compiler (Orcc) is a compiler under BSD license for the RVC-CAL dataflow programming language. Please consult the project homepage at http://orcc.sourceforge.net for more information.
-
11
PARUS
Dataflow parallel programming language for clusters
PARUS is a data-flow parallel programming language that allows to build parallel programs for clusters and MPP multiprocessors. The data-flow graph is automatically converted to the C++/MPI source and linked with the libparus runtime library. Also there are available tools for benchmarking cluster interconnect and visualize it. -
12
A graphical process designer and engine extension for JBoss jBPM with dataflow capabilities, common task nodes: SQL, FTP, R (Stats), Groovy and email and round-trip process engineering/management from an Eclipse-based editor
-
13
-
14
An environment for building and executing actor/dataflow models, including support for the CAL actor language.
-
15
Ohua is an implementation of the stateful functional programming model along with a dataflow execution engine as a runtime system. Ohua mixes object-oriented (imperative) and functional programming to provide implicit parallelism. The project moved. Please find the most up-to-date version at: https://bitbucket.org/sertel/ohua
-
16
The Squidy Interaction Library eases the design of "post-WIMP" user interfaces by unifying various device drivers, frameworks and tracking toolkits in a common library and provides a central and easy-to-use visual design environment. www.squidy-lib.de
-
17
-
18
Tableflow is a Java web component to connect tabular data using an executable dataflow paradigm. This project includes an advanced data grid component, compatible with JSF that has build in support for filtering, paging, sorting and much more.
- Previous
- You're on page 1
- Next
