Open Source Linux Data Integration Tools
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Data Integration Tools for Linux
View 40 business solutionsBrowse free open source Data Integration tools and projects for Linux below. Use the toggles on the left to filter open source Data Integration tools by OS, license, language, programming language, and project status.
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Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
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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.
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Pentaho
Pentaho offers comprehensive data integration and analytics platform.
Pentaho couples data integration with business analytics in a modern platform to easily access, visualize and explore data that impacts business results. Use it as a full suite or as individual components that are accessible on-premise, in the cloud, or on-the-go (mobile). Pentaho enables IT and developers to access and integrate data from any source and deliver it to your applications all from within an intuitive and easy to use graphical tool. The Pentaho Enterprise Edition Free Trial can be obtained from https://pentaho.com/download/ -
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Pentaho Data Integration
Pentaho Data Integration ( ETL ) a.k.a Kettle
Pentaho Data Integration uses the Maven framework. Project distribution archive is produced under the assemblies module. Core implementation, database dialog, user interface, PDI engine, PDI engine extensions, PDI core plugins, and integration tests. Maven, version 3+, and Java JDK 1.8 are requisites. Use of the Pentaho checkstyle format (via mvn checkstyle:check and reviewing the report) and developing working Unit Tests helps to ensure that pull requests for bugs and improvements are processed quickly. In addition to the unit tests, there are integration tests that test cross-module operation. -
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Airbyte
Data integration platform for ELT pipelines from APIs, databases
We believe that only an open-source solution to data movement can cover the long tail of data sources while empowering data engineers to customize existing connectors. Our ultimate vision is to help you move data from any source to any destination. Airbyte already provides the largest catalog of 300+ connectors for APIs, databases, data warehouses, and data lakes. Moving critical data with Airbyte is as easy and reliable as flipping on a switch. Our teams process more than 300 billion rows each month for ambitious businesses of all sizes. Enable your data engineering teams to focus on projects that are more valuable to your business. Building and maintaining custom connectors have become 5x easier with Airbyte. With an average response rate of 10 minutes or less and a Customer Satisfaction score of 96/100, our team is ready to support your data integration journey all over the world. -
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Recap
Recap tracks and transform schemas across your whole application
Recap is a schema language and multi-language toolkit to track and transform schemas across your whole application. Your data passes through web services, databases, message brokers, and object stores. Recap describes these schemas in a single language, regardless of which system your data passes through. Recap schemas can be defined in YAML, TOML, JSON, XML, or any other compatible language. -
Simply solve complex auth. Easy for devs to set up. Easy for non-devs to use.Custom auth drains 25% of dev time and risks 62% more breaches, stalling enterprise deals. Frontegg platform delivers a simple login box, seamless authentication (SSO, MFA, passwordless), robust multi-tenancy, and a customizable Admin Portal. Integrate fast with the React SDK, meet compliance needs, and focus on innovation.
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nango
A single API for all your integrations.
Nango is a single API to interact with all other external APIs. It should be the only API you need to integrate to your app. Nango is an open-source solution for integrating third-party APIs with applications, simplifying API authentication, data syncing, and management. -
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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. This mapping between record key and file group/file id, never changes once the first version of a record has been written to a file. In short, the mapped file group contains all versions of a group of records. -
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Dagster
An orchestration platform for the development, production
Dagster is an orchestration platform for the development, production, and observation of data assets. Dagster as a productivity platform: With Dagster, you can focus on running tasks, or you can identify the key assets you need to create using a declarative approach. Embrace CI/CD best practices from the get-go: build reusable components, spot data quality issues, and flag bugs early. Dagster as a robust orchestration engine: Put your pipelines into production with a robust multi-tenant, multi-tool engine that scales technically and organizationally. Dagster as a unified control plane: The ‘single plane of glass’ data teams love to use. Rein in the chaos and maintain control over your data as the complexity scales. Centralize your metadata in one tool with built-in observability, diagnostics, cataloging, and lineage. Spot any issues and identify performance improvement opportunities. -
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CI Tools Demo
Docker Infrastructure via docker-compose
This repository provides a Docker-powered CI tools demo environment via a single command with docker-compose. It assembles popular CI/CD components—Jenkins, SonarQube, Nexus, GitLab, and Selenium Grid—each running in separate containers, facilitating self-contained integration testing or workshops. It’s not intended for production but serves as a practical demo or launchpad for containerized CI stacks. -
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Alova.js
Workflow-Streamlined next-generation request tools
Extremely streamline API integration workflow. Quickly find APIs in the editor, and enjoy full type hints even in js projects with the API code automatically generated by Alova's extension. Request in various complex scenes by one line of code. Automatically manage paging data, and data preloading, reduce unnecessary data refresh, improve fluency by 300%, and reduce coding difficulty by 50%. Send requests immediately by watching state changes, useful in tab switching and condition querying. Global interceptor that supports silent token refresh, as well as providing unified management of token-based login, logout, token assignment, and token refresh. -
Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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Nest Manager
NST Manager (SmartThings)
Nest-Manager is a community-developed SmartApp (for SmartThings) that integrates Nest thermostat and Protect devices. It provided automation control and monitoring, but has since been archived and is no longer maintained as of April 4, 2023. -
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Searchkick
Intelligent search made easy
Searchkick is a Ruby gem that simplifies adding intelligent, full-text search capabilities to Rails (or other Ruby) applications. It acts as an interface to search engines like Elasticsearch or OpenSearch, letting developers define which models are searchable, how data is indexed, and how queries are performed and refined. It includes features such as typos/misspellings, stemming, custom synonyms, autocomplete, boosting, filtering, and ranking. It supports reindexing and using background jobs for syncing indices. -
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nichenetr
NicheNet: predict active ligand-target links between interacting cells
nichenetr: the R implementation of the NicheNet method. The goal of NicheNet is to study intercellular communication from a computational perspective. NicheNet uses human or mouse gene expression data of interacting cells as input and combines this with a prior model that integrates existing knowledge on ligand-to-target signaling paths. This allows to predict ligand-receptor interactions that might drive gene expression changes in cells of interest. This model of prior information on potential ligand-target links can then be used to infer active ligand-target links between interacting cells. NicheNet prioritizes ligands according to their activity (i.e., how well they predict observed changes in gene expression in the receiver cell) and looks for affected targets with high potential to be regulated by these prioritized ligands. -
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CloverDX
Design, automate, operate and publish data pipelines at scale
Please, visit www.cloverdx.com for latest product versions. Data integration platform; can be used to transform/map/manipulate data in batch and near-realtime modes. Suppors various input/output formats (CSV,FIXLEN,Excel,XML,JSON,Parquet, Avro,EDI/X12,HL7,COBOL,LOTUS, etc.). Connects to RDBMS/JMS/Kafka/SOAP/Rest/LDAP/S3/HTTP/FTP/ZIP/TAR. CloverDX offers 100+ specialized components which can be further extended by creation of "macros" - subgraphs - and libraries, shareable with 3rd parties. Simple data manipulation jobs can be created visually. More complex business logic can be implemented using Clover's domain-specific-language CTL, in Java or languages like Python or JavaScript. Through its DataServices functionality, it allows to quickly turn data pipelines into REST API endpoints. The platform allows to easily scale your data job across multiple cores or nodes/machines. Supports Docker/Kubernetes deployments and offers AWS/Azure images in their respective marketplace -
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Open Source Data Quality and Profiling
World's first open source data quality & data preparation project
This project is dedicated to open source data quality and data preparation solutions. Data Quality includes profiling, filtering, governance, similarity check, data enrichment alteration, real time alerting, basket analysis, bubble chart Warehouse validation, single customer view etc. defined by Strategy. This tool is developing high performance integrated data management platform which will seamlessly do Data Integration, Data Profiling, Data Quality, Data Preparation, Dummy Data Creation, Meta Data Discovery, Anomaly Discovery, Data Cleansing, Reporting and Analytic. It also had Hadoop ( Big data ) support to move files to/from Hadoop Grid, Create, Load and Profile Hive Tables. This project is also known as "Aggregate Profiler" Resful API for this project is getting built as (Beta Version) https://sourceforge.net/projects/restful-api-for-osdq/ apache spark based data quality is getting built at https://sourceforge.net/projects/apache-spark-osdq/ -
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Metl ETL Data Integration
Simple message-based, web-based ETL integration
Metl is a simple, web-based ETL tool that allows for data integrations including database, files, messaging, and web services. Supports RDBMS, SOAP, HTTP, FTP, SFTP, XML, FIXLEN, CSV, JSON, ZIP, and more. Metl implements scheduled integration tasks without the need for custom coding or heavy infrastructure. It can be deployed in the cloud or in an internal data center, and it was built to allow developers to extend it with custom components. -
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COMA Community Edition
Schema Matching Solution for Data Integration
COMA CE is the community edition of the well-established COMA project developed at the University of Leipzig. It comprises the parsers, matcher library, matching framework and a sample GUI for tests and evaluations. COMA was initiated at the database chair of the University of Leipzig in 2002 and got much positive feedback ever since. It excels due to numerous matching strategies, which can be combined to large matching workflows, and which enable reliable match results between different kind of schemas. -
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Jaspersoft ETL is a data integration platform providing high performance data extract-transform-load (ETL) capabilities. Jaspersoft ETL is appropriate for all analytic and operational data integration needs. Activity on this project is located at jas
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PaloKettlePlugin is for Pentaho Data Integration aka Kettle. It's a Cell Input und Output Step for Palo Molap. The first code was developed by mybiq/3A-Strategy, the PDI-3 version has been developed by Stratebi. Now by 3A-Strategy and Litebi for PDI
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Templates for integrating the data structures of Compiere, Openbravo or ADempiere for all kind of Pentaho Data Integration processes. Later on we plan to migrate these to Talend too.
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The Stem Cell Artificial Neural network project entails the analysis and integration of genomics data for extracting the stemness signature of several tissues by training a multiclass single-layer linear artificial neural network.
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ARSystem plugins for Pentaho Kettle
AR-System step and db plugins for Pentaho Data Integration Kettle V5
Allows you to write per API to AR-System Server (BMC Remedy Action Request System). Includes two step output, one step input and one database plugin. The step plugins need the database plugin. -
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AWS data tools
AWS tools for data integration and more
Here I list some data tools I created for Amazon AWS S3 and Redshift -
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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. You can ask Apache DevLake many questions regarding your development process. Just connect and query. Your Dev Data lives in many silos and tools. DevLake brings them all together to give you a complete view of your Software Development Life Cycle (SDLC). From DORA to scrum retros, DevLake implements metrics effortlessly with prebuilt dashboards supporting common frameworks and goals. DevLake fits teams of all shapes and sizes, and can be readily extended to support new data sources, metrics, and dashboards, with a flexible framework for data collection and transformation.
