Search Results for "data-integration" - Page 3
Sort By:
Showing 36029 open source projects for "data-integration"
View related business solutions-
$300 in Free Credit Towards Top Cloud ServicesStart your project in minutes. After credits run out, 20+ products include free monthly usage. Only pay when you're ready to scale.
-
Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
-
1
Spring Data REST
Simplifies building hypermedia-driven REST web services
Spring Data REST is part of the umbrella Spring Data project and makes it easy to build hypermedia-driven REST web services on top of Spring Data repositories. Spring Data REST builds on top of Spring Data repositories, analyzes your application’s domain model and exposes hypermedia-driven HTTP resources for aggregates contained in the model. -
2
Spring Data MongoDB
Provide support to increase developer productivity in Java
...The Spring Data MongoDB project provides integration with the MongoDB document database. Key functional areas of Spring Data MongoDB are a POJO-centric model for interacting with a MongoDB Document and easily writing a repository-style data access layer. You do not need to build from source to use Spring Data. Binaries are available in repo.spring.io and accessible from Maven using the Maven configuration noted. -
3
Spring Data Redis
Provides support to increase developer productivity in Java
Provides support to increase developer productivity in Java when using Redis, a key-value store. Uses familiar Spring concepts such as a template class for core API usage and lightweight repository-style data access. The primary goal of the Spring Data project is to make it easier to build Spring-powered applications that use new data access technologies such as non-relational databases, map-reduce frameworks, and cloud-based data services. Connection package as low-level abstraction across multiple Redis drivers (Lettuce and Jedis). Exception translation to Spring’s portable Data Access exception hierarchy for Redis driver exceptions. ... -
4
Spring Data JPA
Simplifies the development of creating a JPA-based data access layer
Spring Data JPA, part of the larger Spring Data family, makes it easy to easily implement JPA-based repositories. This module deals with enhanced support for JPA-based data access layers. It makes it easier to build Spring-powered applications that use data access technologies. Implementing a data access layer of an application has been cumbersome for quite a while. -
Fully Managed MySQL, PostgreSQL, and SQL ServerCloud SQL handles your database ops end to end, so you can focus on your app.
-
5
Data Structures for PHP 7
An extension providing efficient data structures for PHP 7
An extension providing specialized data structures as efficient alternatives to the PHP array. Highlights the API, performance and other benefits. PHP has one data structure to rule them all. The array is a complex, flexible, master-of-none, hybrid data structure, combining the behaviour of a list and a linked map. But we use it for everything, because PHP is pragmatic: “dealing with things sensibly and realistically in a way that is based on practical rather than theoretical considerations”. ... -
6
AWS Data Wrangler
Pandas on AWS, easy integration with Athena, Glue, Redshift, etc.
An AWS Professional Service open-source python initiative that extends the power of Pandas library to AWS connecting DataFrames and AWS data-related services. Easy integration with Athena, Glue, Redshift, Timestream, OpenSearch, Neptune, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON, and EXCEL). Built on top of other open-source projects like Pandas, Apache Arrow and Boto3, it offers abstracted functions to execute usual ETL tasks like load/unload data from Data Lakes, Data Warehouses, and Databases. ... -
7
Cookiecutter Data Science
Project structure for doing and sharing data science work
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work. When we think about data analysis, we often think just about the resulting reports, insights, or visualizations. While these end products are generally the main event, it's easy to focus on making the products look nice and ignore the quality of the code that generates them. Because these end products are created programmatically, code quality is still important! ... -
8
Positron
Positron, a next-generation data science IDE
...The IDE supports notebook and script workflows, integration of data-app frameworks (such as Shiny, Streamlit, Dash), database and cloud connections, and built-in AI-assisted capabilities to help write code, explore data, and build models. -
9
Canal
MySQL binlog
Canal is an open-source project developed by Alibaba that simulates MySQL slave functionality to parse MySQL binlog files. It enables real-time data synchronization and change data capture (CDC) between MySQL and other systems such as Elasticsearch, Kafka, or HBase. Canal is widely used for data integration, replication, and monitoring across distributed systems, offering high performance and low-latency log parsing. -
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.
-
10
DeerFlow
Deep Research framework, combining language models with tools
...It supports asynchronous task coordination, modular tool integration, and orchestrates the data flow between agents — making it suitable for large-scale or multi-stage research pipelines. Users can deploy it locally or on server infrastructure, integrate custom tools, and benefit from its flexible configuration. -
11
reticulate
R Interface to Python
reticulate is an R package from Posit that creates seamless interoperability between R and Python. It lets you call Python modules, classes, and functions from within R, automatically translating between R and Python data structures. Useful for combining Python tooling with R projects, data analysis, and RMarkdown reports. -
12
CellTypist
A tool for semi-automatic cell type classification, harmonization
CellTypist is an automated tool for cell type classification, harmonization, and integration. Classification, transfer cell type labels from the reference to query dataset. Harmonization, match and harmonize cell types defined by independent datasets. integration, integrate cell and cell types with supervision from harmonization. CellTypist recapitulates cell type structure and biology of independent datasets. Regularised linear models with Stochastic Gradient Descent provide a fast and accurate prediction. ... -
13
nodejs-integration-tests-best-practices
Beyond the basics of Node.js testing
Component/integration test is a hybrid between E2E and unit tets. It's gaining a lot of popularity and going by the testing diamond model it is considered as the default technique for the modern backend. Its main idea is testing an entire component (e.g., Microservice) as-is, through the API, with all the layers including the database but fake anything extraneous. -
14
SymbolicNumericIntegration.jl
SymbolicNumericIntegration.jl: Symbolic-Numerics for Solving Integrals
SymbolicNumericIntegration.jl is a hybrid symbolic/numerical integration package that works on the Julia Symbolics expressions. -
15
Ahoy
Simple, powerful, first-party analytics for Rails
Ahoy is a first-party analytics library built primarily for Ruby on Rails, designed to let applications track visits and events in a clean, integrated way rather than relying on third-party tooling. It stores data in your own database by default, which gives developers full control over what data is captured, how it's processed, and how it’s used, sidestepping privacy concerns of external analytics providers. The library supports Rails, JavaScript, and native apps, making it flexible across front-end/back-end and mobile contexts. Because it’s designed for developers who already own their data stack, Ahoy encourages self-hosted analytics workflows, custom reporting, and integration with existing database infrastructure. ... -
16
JavaScript Algo and Data Structures
Algorithms and data structures implemented in JavaScript
javascript-algorithms is an open source repository by Oleksii Trekhleb that provides implementations of algorithms and data structures in JavaScript. Each algorithm includes explanations, complexity analysis, and references for further reading, making it both a coding resource and a study guide. The repository covers topics such as sorting, searching, graph algorithms, cryptography, and data structures like linked lists, stacks, and queues. It is designed to help developers understand algorithm fundamentals and practice problem-solving with JavaScript. ... -
17
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. ... -
18
JSON for Modern C++
JSON that's part of C++
This is JSON for C++, a JSON library unlike any other that's packed with plenty of great features. While there may be dozens of JSON libraries out there, JSON for C++ stands out with a focus on three things: an intuitive syntax, trivial integration and serious testing. Using the operator magic of modern C++, this library makes JSON feel like a first class data type. With trivial integration, the entire code is made up of a single header file json.hpp, no dependencies, no complex build system required. It's been heavily unit-tested covering 100% of the code, and follows the Core Infrastructure Initiative (CII) best practices to ensure the highest quality at all times. ... -
19
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%. -
20
Suna
Suna - Open Source Generalist AI Agent
...Designed to assist users in accomplishing real-world tasks through natural conversation, Suna combines powerful capabilities with an intuitive interface. It serves as a digital companion for research, data analysis, and everyday challenges, integrating tools like browser automation, file management, web crawling, command-line execution, website deployment, and API integration. Suna's architecture comprises a FastAPI-based backend, a Next.js/React frontend, an agent Docker environment, and a Supabase database for state management. This modular design allows for seamless interaction and task execution through simple conversations. -
21
LiteParse
A fast, helpful, and open-source document parser
...LiteParse supports integration with multiple language models, allowing developers to choose the best balance between accuracy and efficiency. It also includes mechanisms for validation and error handling, ensuring that outputs conform to expected schemas and reducing the need for manual postprocessing. The library is particularly useful for tasks such as data extraction, document processing, and building pipelines that require structured outputs from natural language input. -
22
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. -
23
keycloak-config-cli
Import YAML/JSON-formatted configuration files into Keycloak
keycloak-config-cli is a Keycloak utility to ensure the desired configuration state for a realm based on a JSON/YAML file. The format of the JSON/YAML file is based on the export realm format. Store and handle the configuration files inside git just like normal code. A Keycloak restart isn't required to apply the configuration. The config files are based on the keycloak export files. You can use them to re-import your settings. But keep your files as small as possible. Remove all UUIDs and... -
24
APIJSON
Real-Time coding-free, powerful and secure ORM
...It allows developers to perform CRUD operations through JSON-based requests without writing backend code, significantly accelerating development and reducing errors. APIJSON supports fine-grained access control, parameter validation, and seamless integration with various databases, making it a powerful tool for building scalable APIs. -
25
Jan.ai
Open source alternative to ChatGPT that runs 100% offline
Jan.ai is an open-source, privacy-focused AI assistant that serves as an alternative to ChatGPT, running completely locally on your device. It allows you to download and run LLMs (local language models) offline while also offering optional integration with cloud-based model providers—giving you full control over your data and AI interactions. Download and run LLMs (Llama, Gemma, Qwen, GPT-oss etc.) from HuggingFace. Connect to GPT models via OpenAI, Claude models via Anthropic, Mistral, Groq, and others. Create specialized AI assistants for your tasks. MCP integration for agentic capabilities.
