Search Results for "jpk data processing"
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Showing 386 open source projects for "jpk data processing"
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ThingsBoard
Device management, data collection, processing and visualization
...Define relations between your devices, assets, customers or any other entities. Collect and store telemetry data in a scalable and fault-tolerant way. Visualize your data with built-in or custom widgets and flexible dashboards. Share dashboards with your customers. Define data processing rule chains. Transform and normalize your device data. Raise alarms on incoming telemetry events, attribute updates, device inactivity, and user actions. -
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ZXing
Barcode scanning library for Java, Android
ZXing or “Zebra Crossing” is an open source multi-format 1D/2D barcode image processing library that’s been implemented in Java, and also comes with ports to other languages. It currently supports the following formats: UPC-A and UPC-E EAN-8 and EAN-13 Code 39 Code 93 Code 128 ITF Codabar RSS-14 (all variants) RSS Expanded (most variants) QR Code Data Matrix Aztec ('beta' quality) PDF 417 ('alpha' quality) MaxiCode ZXing is made up of several modules, including a core image decoding library, JavaSE-specific client code, and Android client Barcode Scanner. ... -
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Apache Hudi
Upserts, Deletes And Incremental Processing on Big Data
Apache Hudi (pronounced Hoodie) stands for Hadoop Upserts Deletes and Incrementals. Hudi manages the storage of large analytical datasets on DFS (Cloud stores, HDFS or any Hadoop FileSystem compatible storage). Apache Hudi is a transactional data lake platform that brings database and data warehouse capabilities to the data lake. Hudi reimagines slow old-school batch data processing with a powerful new incremental processing framework for low latency minute-level analytics. Hudi provides efficient upserts, by mapping a given hoodie key (record key + partition path) consistently to a file id, via an indexing mechanism. ... -
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Reactor Core
Non-Blocking Reactive Foundation for the JVM
Reactor Core is a foundational library for building reactive applications in Java, providing a powerful API for asynchronous, non-blocking programming. -
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Apache Beam
Unified programming model for Batch and Streaming
Apache Beam is an open source, unified programming model to define both batch and streaming data-parallel processing pipelines, as well as certain language-specific SDKs for constructing pipelines and Runners. 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. -
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Dolphin Scheduler
A distributed and extensible workflow scheduler platform
Apache DolphinScheduler is a distributed and extensible workflow scheduler platform with powerful DAG visual interfaces, dedicated to solving complex job dependencies in the data pipeline and providing various types of jobs available `out of the box`. Dedicated to solving the complex task dependencies in data processing, making the scheduler system out of the box for data processing. Decentralized multi-master and multi-worker, HA is supported by itself, overload processing. All process definition operations are visualized, Visualization process defines key information at a glance, One-click deployment. ... -
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Flink CDC
Flink CDC is a streaming data integration tool
Apache Flink CDC is a distributed data integration tool that captures data changes in real-time from various databases. It leverages Change Data Capture (CDC) technology to stream data changes into Apache Flink, enabling real-time analytics and data processing. Flink CDC simplifies data pipeline development with its declarative YAML configurations. -
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KCloud‑Platform‑IoT
KCloud-Platform-IoT
KCloud-Platform-IoT is a comprehensive open-source IoT management platform built with Spring Cloud and Vue.js. It supports device registration, data collection, rule-based processing, and dashboard visualization. Designed for scalability and modularity, the platform is ideal for managing large IoT fleets in industrial or smart city environments. -
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eXist-db
eXist Native XML Database and Application Platform
eXist-db is an open-source, native XML database and application platform that provides a powerful environment for storing, querying, and managing XML documents. It is designed for complex data management needs, offering XQuery, XSLT, and RESTful web services for interacting with structured data. -
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Logstash
Centralize, transform and stash your data
Logstash is a server-side data processing pipeline that dynamically ingests data from numerous sources, transforms it, and ships it to your favorite “stash” regardless of format or complexity. It supports and ingests data of all shapes, sizes and sources, dynamically transforms and prepares this data, and transports it to the output of your choice. Logstash is extensible, with over 200 plugins available to let you create and configure your pipeline how you choose. -
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PULSAR
Distributed pub-sub messaging system
Apache Pulsar is a cloud-native, distributed messaging and streaming platform originally created at Yahoo! and now a top-level Apache Software Foundation project. Easy to deploy, lightweight compute process, developer-friendly APIs, no need to run your own stream processing engine. Run in production at Yahoo! scale for over 5 years, with millions of messages per second across millions of topics. Expand capacity seamlessly to hundreds of nodes. Low publish latency (< 5ms) at scale with strong durability guarantees. Configurable replication between data centers across multiple geographic regions. Built from the ground up as a multi-tenant system. ... -
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Addax
Addax is a versatile open-source ETL tool
Addax is a data integration and ETL (Extract, Transform, Load) tool designed for high-performance data migration tasks. It simplifies the process of moving data between different systems and formats. -
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Apache Sedona
Cluster computing framework for processing large-scale geospatial data
Apache Sedona™ is a cluster computing system for processing large-scale spatial data. Sedona extends existing cluster computing systems, such as Apache Spark and Apache Flink, with a set of out-of-the-box distributed Spatial Datasets and Spatial SQL that efficiently load, process, and analyze large-scale spatial data across machines. According to our benchmark and third-party research papers, Sedona runs 2X - 10X faster than other Spark-based geospatial data systems on computation-intensive query workloads. ... -
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Qualitis
Qualitis is a one-stop data quality management platform
Qualitis is a data quality management platform that supports quality verification, notification, and management for various datasource. It is used to solve various data quality problems caused by data processing. Based on Spring Boot, Qualitis submits quality model task to Linkis platform. It provides functions such as data quality model construction, data quality model execution, data quality verification, reports of data quality generation and so on. ... -
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Stanford CoreNLP
Stanford CoreNLP, a Java suite of core NLP tools
CoreNLP is your one stop shop for natural language processing in Java! CoreNLP enables users to derive linguistic annotations for text, including token and sentence boundaries, parts of speech, named entities, numeric and time values, dependency and constituency parses, coreference, sentiment, quote attributions, and relations. CoreNLP currently supports 6 languages, Arabic, Chinese, English, French, German, and Spanish. -
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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. -
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Genie
Distributed Big Data Orchestration Service
Genie is a completely open source distributed job orchestration engine developed by Netflix. Genie provides REST-ful APIs to run a variety of big data jobs like Hadoop, Pig, Hive, Spark, Presto, Sqoop and more. It also provides APIs for managing the metadata of many distributed processing clusters and the commands and applications which run on them. -
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Data Crow
The ultimate cataloguer
Data Crow allows you to use the standard movie & video (divx, xvid, DVD, Blu-ray, etc), book (and eBooks), images, board games, comic books, games & software, music (mp3 and other music files) cataloguing modules. Besides these modules, which you can change to fit your requirements, you can create new modules (want to catalogue your stamps, equipment, or anything else?). The GUI is skinnable. Reporting (using JasperReports and their community edition JasperSoft Developer Studio ), loan... -
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Kestra
Kestra is an infinitely scalable orchestration and scheduling platform
Build reliable workflows, blazingly fast, deploy in just a few clicks. Kestra is an open-source, event-driven orchestrator that simplifies data operations and improves collaboration between engineers and business users. By bringing Infrastructure as Code best practices to data pipelines, Kestra allows you to build reliable workflows and manage them with confidence. Thanks to the declarative YAML interface for defining orchestration logic, everyone who benefits from analytics can participate... -
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ANTLR
Parser generator to read, process, or translate structured text
...The languages for Hive and Pig, the data warehouse and analysis systems for Hadoop, both use ANTLR. Lex Machina uses ANTLR for information extraction from legal texts. Oracle uses ANTLR within SQL Developer IDE and their migration tools. NetBeans IDE parses C++ with ANTLR. The HQL language in the Hibernate object-relational mapping framework is built with ANTLR. -
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Hazelcast
Open-source distributed computation and storage platform
...You can deploy it at any scale from small edge devices to a large cluster of cloud instances. A cluster of Hazelcast nodes share both the data storage and computational load which can dynamically scale up and down. When you add new nodes to the cluster, the data is automatically rebalanced across the cluster and currently running computational tasks (known as jobs) snapshot their state and scale with processing guarantees. -
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Apache InLong
Apache InLong - a one-stop integration framework for massive data
Apache InLong is a one-stop integration framework for massive data that provides automatic, secure and reliable data transmission capabilities. InLong supports both batch and stream data processing at the same time, which offers great power to build data analysis, modeling and other real-time applications based on streaming data. InLong (应龙) is a divine beast in Chinese mythology who guides the river into the sea, and it is regarded as a metaphor of the InLong system for reporting data streams. ... -
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Planetiler
Flexible tool to build planet-scale vector tilesets
Planetiler (pla·nuh·tai·lr, formerly named "Flatmap") is a tool that generates Vector Tiles from geographic data sources like OpenStreetMap. Planetiler aims to be fast and memory-efficient so that you can build a map of the world in a few hours on a single machine without any external tools or database. Vector tiles contain raw point, line, and polygon geometries that clients like MapLibre can use to render custom maps in the browser, native apps, or on a server. Planetiler packages tiles... -
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Siddhi Core Libraries
Stream Processing and Complex Event Processing Engine
Fully open source, cloud-native, scalable, micro streaming, and complex event processing system capable of building event-driven applications for use cases such as real-time analytics, data integration, notification management, and adaptive decision-making. Event processing logic can be written using Streaming SQL queries via graphical and source editors, to capture events from diverse data sources, process and analyze them, integrate with multiple services and data stores, and publish output to various endpoints in real time. ... -
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Spring Batch
Spring Batch is a framework for writing batch applications using Java
A lightweight, comprehensive batch framework designed to enable the development of robust batch applications vital for the daily operations of enterprise systems. Spring Batch provides reusable functions that are essential in processing large volumes of records, including logging/tracing, transaction management, job processing statistics, job restart, skip, and resource management. It also provides more advanced technical services and features that will enable extremely high-volume and high...
