
RaimaDB, an embedded time series database that can be used for Edge and IoT devices, can run in-memory. It is a lightweight, secure, and extremely powerful RDBMS. It has been field tested by more than 20 000 developers around the world and has been deployed in excess of 25 000 000 times.
RaimaDB is a high-performance, cross-platform embedded database optimized for mission-critical applications in industries such as IoT and edge computing. Its lightweight design makes it ideal for resource-constrained environments, supporting both in-memory and persistent storage options. RaimaDB offers flexible data modeling, including traditional relational models and direct relationships through network model sets. With ACID-compliant transactions and advanced indexing methods like B+Tree, Hash Table, R-Tree, and AVL-Tree, it ensures data reliability and efficiency. Built for real-time processing, it incorporates multi-version concurrency control (MVCC) and snapshot isolation, making it a robust solution for applications demanding speed and reliability.
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SurveyJS is a set of four open-source JavaScript libraries that offer the benefits of a tailor-made in-house survey application, while considerably reducing the time and resources needed to deploy the system. These libraries are independent of specific server code or database requirements and seamlessly integrate with popular JavaScript frameworks, including React, Angular, Vue.js, jQuery, Knockout, and more. They are designed to communicate with any server that can handle JSON requests, ensuring compatibility with various server architectures and databases.
The product family is composed of:
- An open-source MIT-licensed rendering library that renders dynamic JSON-based forms in your web application, and collects responses.
- A self-hosted drag & drop form builder that features an integrated CSS-based theme editor and a GUI for conditional rules. It automatically generates JSON definitions (schemas) of your forms in real time.
- PDF Generator, a library that renders SurveyJS surveys and forms as PDF files in a browser;
- The Dashboard library that allows you to simplify survey data analysis with interactive and customizable charts and tables.
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Vaex
At Vaex.io, our mission is to make big data accessible to everyone, regardless of the machine or scale they are using. By reducing development time by 80%, we transform prototypes directly into solutions. Our platform allows for the creation of automated pipelines for any model, significantly empowering data scientists in their work. With our technology, any standard laptop can function as a powerful big data tool, eliminating the need for clusters or specialized engineers. We deliver dependable and swift data-driven solutions that stand out in the market. Our cutting-edge technology enables the rapid building and deployment of machine learning models, outpacing competitors. We also facilitate the transformation of your data scientists into proficient big data engineers through extensive employee training, ensuring that you maximize the benefits of our solutions. Our system utilizes memory mapping, an advanced expression framework, and efficient out-of-core algorithms, enabling users to visualize and analyze extensive datasets while constructing machine learning models on a single machine. This holistic approach not only enhances productivity but also fosters innovation within your organization.
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Polars
Polars offers a comprehensive Python API that reflects common data wrangling practices, providing a wide array of functionalities for manipulating DataFrames through an expression language that enables the creation of both efficient and clear code. Developed in Rust, Polars makes deliberate choices to ensure a robust DataFrame API that caters to the Rust ecosystem's needs. It serves not only as a library for DataFrames but also as a powerful backend query engine for your data models, allowing for versatility in data handling and analysis. This flexibility makes it a valuable tool for data scientists and engineers alike.
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