Search Results for "apache open office"
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Showing 294 open source projects for "apache open office"
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Apache HBase
Get random, realtime read/write access to your Big Data
Use Apache HBase™ when you need random, realtime read/write access to your Big Data. This project's goal is the hosting of very large tables, billions of rows X millions of columns, atop clusters of commodity hardware. Apache HBase is an open-source, distributed, versioned, non-relational database modeled after Google's Bigtable. A Distributed Storage System for Structured Data by Chang et al. -
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Apache Polaris
Apache Polaris, the interoperable, open source catalog
Apache Polaris is an open-source metadata catalog and data management service designed to manage Apache Iceberg tables in modern data lakehouse environments. It provides a centralized catalog that allows multiple compute engines and analytics systems to interact with the same datasets through a standardized interface. By implementing the Iceberg REST catalog API, Polaris enables distributed data platforms to access shared table metadata without tightly coupling storage systems and query engines. ... -
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Apache RocketMQ
Distributed messaging and streaming platform with low latency
Apache RocketMQ is a distributed messaging and streaming platform with low latency, high performance and reliability, trillion-level capacity and flexible scalability. Messaging patterns including publish/subscribe, request/reply and streaming. Financial grade transactional message. Built-in fault tolerance and high availability configuration options base on DLedger. A variety of cross language clients, such as Java, C/C++, Python, Go. Pluggable transport protocols, such as TCP, SSL, AIO.... -
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Apache DevLake
Apache DevLake is an open-source dev data platform
Apache DevLake is an open-source dev data platform that ingests, analyzes, and visualizes the fragmented data from DevOps tools to extract insights for engineering excellence, developer experience, and community growth. Apache DevLake is designed for developer teams looking to make better sense of their development process and to bring a more data-driven approach to their own practices. -
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Apache Seata
High-performance, open source distributed transaction solution
Seata is a distributed transaction solution for microservices that provides consistent, cross-service commits without forcing every team to adopt the same persistence model. Its architecture separates responsibilities into a global coordinator and per-service participants, so business services remain decoupled while transactions are orchestrated centrally. Multiple modes are supported—AT (automatic, SQL-based with undo logs), TCC (try-confirm-cancel), Saga (long-running compensation), and... -
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Apache SeaTunnel
SeaTunnel is a distributed, high-performance data integration platform
SeaTunnel is a very easy-to-use ultra-high-performance distributed data integration platform that supports real-time synchronization of massive data. It can synchronize tens of billions of data stably and efficiently every day, and has been used in the production of nearly 100 companies. There are hundreds of commonly-used data sources of which versions are incompatible. With the emergence of new technologies, more data sources are appearing. It is difficult for users to find a tool that can... -
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Apache Doris
MPP-based interactive SQL data warehousing for reporting and analysis
Apache Doris is a modern MPP analytical database product. It can provide sub-second queries and efficient real-time data analysis. With it's distributed architecture, up to 10PB level datasets will be well supported and easy to operate. Apache Doris can meet various data analysis demands, including history data reports, real-time data analysis, interactive data analysis, and exploratory data analysis. Make your data analysis easier! Support standard SQL language, compatible with MySQL... -
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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... -
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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... -
AI-generated apps that pass security reviewRetool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
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Apache Airflow Provider
Great Expectations Airflow operator
Due to apply_default decorator removal, this version of the provider requires Airflow 2.1.0+. If your Airflow version is 2.1.0, and you want to install this provider version, first upgrade Airflow to at least version 2.1.0. Otherwise, your Airflow package version will be upgraded automatically, and you will have to manually run airflow upgrade db to complete the migration. This operator currently works with the Great Expectations V3 Batch Request API only. If you would like to use the... -
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.NET for Apache Spark
A free, open-source, and cross-platform big data analytics framework
.NET for Apache Spark provides high-performance APIs for using Apache Spark from C# and F#. With these .NET APIs, you can access the most popular Dataframe and SparkSQL aspects of Apache Spark, for working with structured data, and Spark Structured Streaming, for working with streaming data. .NET for Apache Spark is compliant with .NET Standard - a formal specification of .NET APIs that are common across .NET implementations. This means you can use .NET for Apache Spark anywhere you write... -
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CyberChef
A web app for encryption, encoding, compression and data analysis
CyberChef, developed by GCHQ, is a versatile web application dubbed the "Cyber Swiss Army Knife." It enables users to perform a wide array of operations on data, including encryption, encoding, compression, and analysis, all within a browser interface. -
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IoTDB
Apache IoTDB
Apache IoTDB (Database for Internet of Things) is an IoT native database with high performance for data management and analysis, deployable on the edge and the cloud. Due to its light-weight architecture, high performance and rich feature set together with its deep integration with Apache Hadoop, Spark and Flink, Apache IoTDB can meet the requirements of massive data storage, high-speed data ingestion and complex data analysis in the IoT industrial fields. In the scene of factories, there... -
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Superset
Apache Superset is a data visualization and data exploration platform
Apache Superset is a modern data exploration and visualization platform. Superset is fast, lightweight, intuitive, and loaded with options that make it easy for users of all skill sets to explore and visualize their data, from simple line charts to highly detailed geospatial charts. Quickly and easily integrate and explore your data, using either our simple no-code viz builder or state-of-the-art SQL IDE. Superset can connect to any SQL-based data source through SQLAlchemy, including modern... -
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Scio
A Scala API for Apache Beam and Google Cloud Dataflow
Scio is a Scala API developed by Spotify that builds on Apache Beam to enable expressive batch and streaming data pipelines, optimized for running on Google Cloud Dataflow. Inspired by Spark and Scalding, it provides scalable, type‑safe, and production-grade data processing, with built-in support for BigQuery, Pub/Sub, Cassandra, Elasticsearch, Redis, TensorFlow IO, and more. -
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Arrow Julia
Official Julia implementation of Apache Arrow
This is a pure Julia implementation of the Apache Arrow data standard. This package provides Julia AbstractVector objects for referencing data that conforms to the Arrow standard. This allows users to seamlessly interface Arrow formatted data with a great deal of existing Julia code. -
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Cassandra Spark Connector
Apache Spark to Apache Cassandra connector
The Apache Cassandra Spark Connector allows Spark jobs (RDDs or DataFrames/Datasets) to read from and write to Cassandra tables. Compatible with Apache Cassandra (v2.1+), Spark 1.0–3.5, and Scala 2.11–2.13, it supports mapping Cassandra rows to Scala case classes, saving results back to Cassandra, and executing arbitrary CQL within Spark applications. -
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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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Karpor
World's most promising Kubernetes Visualization Tool
Karpor is Intelligence for Kubernetes. It brings advanced Search, Insight and AI to Kubernetes. It is essentially a Kubernetes Visualization Tool. With Karpor, you can gain crucial visibility into your Kubernetes clusters across any clouds. -
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Perspective
A data visualization and analytics component
Perspective is a high-performance data visualization library for building real-time, interactive analytics dashboards. Developed by FINOS, it supports WebAssembly-powered pivot tables and can handle large streaming datasets with speed and flexibility. Perspective is ideal for fintech, trading, and IoT applications where insights from live data need to be visualized, sliced, and explored quickly in a browser. -
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Fluid
Fluid, elastic data abstraction and acceleration for BigData/AI apps
Fluid, elastic data abstraction and acceleration for BigData/AI applications in the cloud. Provide DataSet abstraction for underlying heterogeneous data sources with multidimensional management in a cloud environment. Enable dataset warmup and acceleration for data-intensive applications by using a distributed cache in Kubernetes with observability, portability, and scalability. Taking characteristics of application and data into consideration for cloud application/dataset scheduling to... -
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YAO
Yao A low code engine to create web services and dashboard
Yao allows developers to create web services by processes. Yao is a low-code engine that creates a database model, writes API services, and describes dashboard interface just by JSON for web & hardware, no code, and 10x productivity. Yao is based on the flow-based programming idea, developed in the Go language, and supports multiple ways to expand the data stream processor. This makes Yao extremely versatile, which can replace programming languages in most scenarios, and is 10 times more... -
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Kibana
Your window into the Elastic Stack
Kibana is a analytics and search dashboard for Elasticsearch that allows you to visualize Elasticsearch data and efficiently navigate the Elastic Stack. With Kibana you can visualize and shape your data simply and intuitively, share visualizations for greater collaboration, organize dashboards and visualizations, and so much more. -
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JuiceFS
JuiceFS is a distributed POSIX file system built on top of Redis
A POSIX, HDFS and S3 compatible distributed file system for cloud. JuiceFS is designed to bring back the gold-old memories and experience of file systems in local disks to the cloud. JuiceFS is POSIX compliant and is fully compatible with HDFS and S3. Cloud app building or migrating, file sharing cross-geo and cross-cloud has become easier than ever before. Whether it's a public cloud, private cloud, or hybrid cloud, JuiceFS is available on any cloud of your choice and delivers flexibility,... -
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sparklyr
R interface for Apache Spark
sparklyr is an R package that provides seamless interfacing with Apache Spark clusters—either local or remote—while letting users write code in familiar R paradigms. It supplies a dplyr-compatible backend, Spark machine learning pipelines, SQL integration, and I/O utilities to manipulate and analyze large datasets distributed across cluster environments.
