Open Source Linux Data Management Systems
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Data Management Systems for Linux
View 514 business solutionsBrowse free open source Data Management systems and projects for Linux below. Use the toggles on the left to filter open source Data Management systems by OS, license, language, programming language, and project status.
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TurboVNC
High-speed, 3D-friendly, TightVNC-compatible remote desktop software
TurboVNC is a high-performance, enterprise-quality version of VNC based on TightVNC, TigerVNC, and X.org. It contains a variant of Tight encoding that is tuned for maximum performance and compression with 3D applications (VirtualGL), video, and other image-intensive workloads. TurboVNC, in combination with VirtualGL, provides a complete solution for remotely displaying 3D applications with interactive performance. TurboVNC's high-speed encoding methods have been adopted by TigerVNC and libvncserver, and TurboVNC is also compatible with any other TightVNC derivative. TurboVNC forked from TightVNC in 2004 and still covers all of the TightVNC 1.3.x features, but TurboVNC contains numerous feature enhancements and bug fixes relative to TightVNC, and it compresses 3D and video workloads much better than TightVNC while using generally only 5-20% of the CPU time of the latter. Using non-default settings, TurboVNC can also be made to compress 2D workloads as "tightly" as TightVNC. -
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Gephi
Gephi the open graph Viz platform
Gephi is the leading visualization and exploration software for all kinds of graphs and networks. Gephi is open-source and free. Gephi is an award-winning open-source platform for visualizing and manipulating large graphs. It runs on Windows, Mac OS X and Linux. Localization is available in English, French, Spanish, Japanese, Russian, Brazilian Portuguese, Chinese, Czech and German. Fast Powered by a built-in OpenGL engine, Gephi is able to push the envelope with very large networks. Visualize networks up to a million elements. All actions (e.g. layout, filter, drag) run in real-time. Simple Easy to install and get started. An UI that is centered around the visualization. Like Photoshop™ for graphs. Modular Extend Gephi with plug-ins. The architecture is built on top of Apache Netbeans Platform and can be extended or reused easily through well-written APIs. -
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Serial Studio
Multi-purpose serial data visualization & processing
Serial Studio is a simple, multi-platform, and multi-purpose serial data visualization program that allows embedded developers to visualize, analyze, and present data generated from their projects and devices while avoiding the need to write project-specific visualization software. Over my many CanSat-based competitions, I found myself writing and maintaining several Ground Station software for each program. However, I decided that it would be easier and more sustainable to define one flexible Ground Station Software that lets developers define how each CanSat presents data using an extensible communication protocol for easy data visualization. Developers can also use Serial Studio for almost any data acquisition and visualization project outside of CanSat, now supporting data retrieval from hardware serial ports, software serial ports, MQTT, and network sockets (TCP/UDP). You can download and install Serial Studio for your preferred platform. -
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Lossless compressor for multichannel 8,16 and 24 bits audio data, with the ability of password data protection. Being 'lossless' means that no data/quality is lost in the compression - when uncompressed, the data will be identical to the original.
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Elasticsearch
A Distributed RESTful Search Engine
Elasticsearch is a distributed, RESTful search and analytics engine that lets you store, search and analyze with ease at scale. It lets you perform and combine many types of searches; it scales seamlessly, and offers answers incredibly fast with search results you can rank based on a variety of factors. Elasticsearch can be used for a wide variety of use cases, from maps and metrics to site search and workplace search, and with all data types. -
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Azure Data Studio
A data management tool that enables working with other SQL tools
Azure Data Studio is a cross-platform database tool for data professionals who use on-premises and cloud data platforms on Windows, macOS, and Linux. Azure Data Studio offers a modern editor experience with IntelliSense, code snippets, source control integration, and an integrated terminal. It's engineered with the data platform user in mind, with the built-in charting of query result sets and customizable dashboards. Use Azure Data Studio to query, design, and manage your databases and data warehouses wherever they are, on your local computer or in the cloud. Azure Data Studio offers a modern, keyboard-focused SQL coding experience that makes your everyday tasks easier with built-in features, such as multiple tab windows, a rich SQL editor, IntelliSense, keyword completion, code snippets, code navigation, and source control integration (Git). -
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EtherApe is a graphical network monitor modeled after etherman. Featuring Ethernet, IP, TCP, FDDI, Token Ring and wireless modes, it displays network activity graphically. Hosts and links change in size with traffic. Color coded protocols display.
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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. Just as Bigtable leverages the distributed data storage provided by the Google File System, Apache HBase provides Bigtable-like capabilities on top of Hadoop and HDFS. Thrift gateway and a REST-ful Web service that supports XML, Protobuf, and binary data encoding options. Support for exporting metrics via the Hadoop metrics subsystem to files or Ganglia; or via JMX. Convenient base classes for backing Hadoop MapReduce jobs with Apache HBase tables. -
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SDGym
Benchmarking synthetic data generation methods
The Synthetic Data Gym (SDGym) is a benchmarking framework for modeling and generating synthetic data. Measure performance and memory usage across different synthetic data modeling techniques – classical statistics, deep learning and more! The SDGym library integrates with the Synthetic Data Vault ecosystem. You can use any of its synthesizers, datasets or metrics for benchmarking. You also customize the process to include your own work. Select any of the publicly available datasets from the SDV project, or input your own data. Choose from any of the SDV synthesizers and baselines. Or write your own custom machine learning model. In addition to performance and memory usage, you can also measure synthetic data quality and privacy through a variety of metrics. Install SDGym using pip or conda. We recommend using a virtual environment to avoid conflicts with other software on your device. -
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The aoetools are programs for users of the ATA over Ethernet (AoE) network storage protocol, a simple protocol for using storage over an ethernet LAN. The vblade program (storage target) exports a block device using AoE.
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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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MyCAT
Active, high-performance open source database middleware
MyCAT is an Open-Source software, “a large database cluster” oriented to enterprises. MyCAT is an enforced database which is a replacement for MySQL and supports transaction and ACID. Regarded as MySQL cluster of enterprise database, MyCAT can take the place of expensive Oracle cluster. MyCAT is also a new type of database, which seems like a SQL Server integrated with the memory cache technology, NoSQL technology and HDFS big data. And as a new modern enterprise database product, MyCAT is combined with the traditional database and new distributed data warehouse. In a word, MyCAT is a fresh new middleware of database. MyCAT ’s objective is to smoothly migrate the current stand-alone database and applications to cloud side with low cost and to solve the bottleneck problem caused by the rapid growth of data storage and business scale. -
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DAT Linux
The data science OS
DAT Linux is a Linux distribution for data science. It brings together all your favourite open-source data science tools and apps into a ready-to-run desktop environment. https://datlinux.com It's based on Lubuntu, so it’s easy to install and use. The custom DAT Linux Control Panel provides a centralised one-stop-shop for running and managing dozens of data science programs. DAT Linux is perfect for students, professionals, academics, or anyone interested in data science who doesn’t want to spend endless hours downloading, installing, configuring, and maintaining applications from a range of sources, each with different technical requirements and set-up challenges. -
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OSHMI - Open Substation HMI
SCADA HMI for substations, IoT and automation applications
Now with IEC61850 support! This project combines existing open source projects and tools to create a very capable, mobile and cloud-friendly HMI system that can rival proprietary software. This approach makes it possible to join forces of each project (Chromium, SVG/HTML5, PHP, Lua, SQLite, Inkscape, Lib61850, OpenDNP3, Nginx, Vega, PostgreSQL, Grafana,…) to achieve a great set of open, evergreen, modular and customizable tools for building great HMIs for automation projects. This is not a toy project! It's been actually used in dozens of substations up to 230kV level and also in control centers with configurations up to 70.000 tags. Feel free to ask questions in the "Discussion" section. Help sponsoring OSHMI here https://github.com/sponsors/riclolsen. >>> Have a look also at my new SCADA project here: https://github.com/riclolsen/json-scada -
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Akka
Build concurrent, distributed, and resilient message-driven apps
Build powerful reactive, concurrent, and distributed applications more easily. Akka is a toolkit for building highly concurrent, distributed, and resilient message-driven applications for Java and Scala. Actors and Streams let you build systems that scale up, using the resources of a server more efficiently, and out, using multiple servers. Building on the principles of The Reactive Manifesto Akka allows you to write systems that self-heal and stay responsive in the face of failures. Up to 50 million msg/sec on a single machine. Small memory footprint; ~2.5 million actors per GB of heap. Distributed systems without single points of failure. Load balancing and adaptive routing across nodes. Event Sourcing and CQRS with Cluster Sharding. Distributed Data for eventual consistency using CRDTs. Asynchronous non-blocking stream processing with backpressure. -
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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. Built-in message tracing capability, also support opentracing. Versatile big-data and streaming ecosytem integration. Message retroactivity by time or offset. Reliable FIFO and strict ordered messaging in the same queue. Efficient pull and push consumption model. Million-level message accumulation capacity in a single queue. Multiple messaging protocols like JMS and OpenMessaging. Flexible distributed scale-out deployment architecture. Lightning-fast batch message exchange system. -
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Arize Phoenix
Uncover insights, surface problems, monitor, and fine tune your LLM
Phoenix provides ML insights at lightning speed with zero-config observability for model drift, performance, and data quality. Phoenix is an Open Source ML Observability library designed for the Notebook. The toolset is designed to ingest model inference data for LLMs, CV, NLP and tabular datasets. It allows Data Scientists to quickly visualize their model data, monitor performance, track down issues & insights, and easily export to improve. Deep Learning Models (CV, LLM, and Generative) are an amazing technology that will power many of future ML use cases. A large set of these technologies are being deployed into businesses (the real world) in what we consider a production setting. -
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fluentbit
Fast and Lightweight Logs and Metrics processor for Linux, BSD, OSX
Fluent Bit is a super-fast, lightweight, and highly scalable logging and metrics processor and forwarder. It is the preferred choice for cloud and containerized environments. A robust, lightweight, and portable architecture for high throughput with low CPU and memory usage from any data source to any destination. Proven across distributed cloud and container environments. Highly available with I/O handlers to store data for disaster recovery. Granular management of data parsing and routing. Filtering and enrichment to optimize security and minimize cost. The lightweight, asynchronous design optimizes resource usage: CPU, memory, disk I/O, network. No more OOM errors! Integration with all your technology, cloud-native services, containers, streaming processors, and data backends. Fully event-driven design leverages the operating system API for performance and reliability. All operations to collect and deliver data are asynchronous. -
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lakeFS
lakeFS - Git-like capabilities for your object storage
Increase data quality and reduce the painful cost of errors. Data engineering best practices using git-like operations on data. lakeFS is an open-source data version control for data lakes. It enables zero-copy Dev / Test isolated environments, continuous quality validation, atomic rollback on bad data, reproducibility, and more. Data is dynamic, it changes over time. Dealing with that without a data version control system is error-prone and labor-intensive. With lakeFS, your data lake is version controlled and you can easily time-travel between consistent snapshots of the lake. Easier ETL testing - test your ETLs on top of production data, in isolation, without copying anything. Safely experiment and test on full production data. Easily Collaborate on production data with your team. Automate data quality checks within data pipelines. -
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FlowViewer
FlowViewer is a web-based netflow data analysis tool.
FlowViewer provides a convenient web-based user interface to Mark Fullmer’s flow-tools suite and CMU's netflow data capture/analyzer, SiLK. The inclusion of the underlying SiLK tool set enables FlowViewer users to continue to use the tool with the newer IPFIX netflow data protocol, which includes support for IPv6 and Cisco's v9 and FNF netflow. FlowViewer has been developed for NASA’s Earth Sciences Data and Information System (ESDIS) networks, and credit goes to NASA for their usual outstanding support of innovation. The FlowViewer tools provide additional graphing and tracking features by utilizing open source software including Thomas Boutrell’s gd, Lincoln Stein's GD, Martien Verbruggen's GD::Graph, and Tobias Oetiker’s RRDtool. FlowViewer v4.6 fixes non-UTC local time environments for FlowViewer and FlowGrapher, and $no_devices_or_exporters FlowMonitor_Collector problem. **Note: SiLK must be v3.8.0 or later. Version 3.9 handles sFlow data. -
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jpcap is a set of Java classes which provide an interface and system for network packet capture. A protocol library and tool for visualizing network traffic is included. jpcap utilizes libpcap, a widely deployed system library for packet capture.
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CapAnalysis
PCAP from another point of view
CapAnalysis is a web visual tool for information security specialists, system administrators and everyone who needs to analyze large amounts of captured network traffic. Analyze TCP and UDP streams Support multible datasets Perform deep packet inspection Support filtering capability Source Code: https://github.com/xplico/CapAnalysis -
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Alluxio
Open Source Data Orchestration for the Cloud
Alluxio is the world’s first open source data orchestration technology for analytics and AI for the cloud. It bridges the gap between computation frameworks and storage systems, bringing data from the storage tier closer to the data driven applications. This enables applications to connect to numerous storage systems through a common interface. It makes data local, more accessible and as elastic as compute. -
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Broot
A new way to see and navigate directory trees
Get an overview of a directory, even a big one. That's what makes it usable where the old tree command would produce pages of output. Hit alt/enter and you're back to the terminal in the desired location. This way, you can navigate to a directory with the minimum amount of keystrokes, even if you don't exactly remember where it is. Broot is fast and doesn't block (any keystroke interrupts the current search to start the next one). Never lose track of file hierarchy while you search. Broot tries to select the most relevant file. You can still go from one match to another one using tab or arrow keys. You may also search with a regular expression. To do this, add a / before the pattern. You may also apply logical operators or combine patterns, for example searching test in all files except json ones could be !/json$/&c/test and searching carg both in file names and file contents would be carg|c/carg. -
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Cytoscape.js
Graph theory library for visualization and analysis
A fully featured graph library written in pure JS. Permissive open source license (MIT) for the core Cytoscape.js library and all first-party extensions. Used in commercial projects and open-source projects in production. Designed for users first, for both frontfacing app usecases and developer usecases. Highly optimized. Compatible with All modern browsers. Legacy browsers with ES5 and canvas support. ES5 and canvas support are required, and feature detection is used for optional performance enhancements. Browsers circa 2012 support ES5 fully: IE10, Chrome 23, Firefox 21, Safari 6 (caniuse). Browsers with partial but sufficient ES5 support also work, such as IE9 and Firefox 4. The documentation and examples are not optimized for old browsers, although the library itself is. Some demos may not work in old browsers in order to keep the demo code simple.