
SurveyJS comprises a collection of four open-source JavaScript libraries that provide the advantages of a customized, in-house survey application while significantly minimizing the time and resources required for deployment. These libraries function independently of specific server code or database needs, allowing for seamless integration with well-known JavaScript frameworks such as React, Angular, Vue.js, jQuery, Knockout, and others. They are built to interact with any server capable of processing JSON requests, thereby ensuring compatibility with a wide range of server setups and databases.
This product suite includes:
- An open-source library licensed under MIT that facilitates the rendering of dynamic JSON-based forms within your web application and captures user responses.
- A self-hosted form builder featuring drag-and-drop functionality, an integrated CSS theme editor, and a graphical user interface for setting conditional rules; it also generates JSON definitions of your forms in real time.
- A PDF Generator library that allows for the conversion of SurveyJS surveys and forms into PDF files directly in the browser.
- The Dashboard library, which enhances survey data analysis through interactive and customizable charts and tables.
We invite you to explore our website and experience our comprehensive demo at no cost. This opportunity will allow you to assess the full capabilities of SurveyJS firsthand.
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Headquartered in Victoria, British Columbia and founded in 2016, Shift is a Certified B Corp and part of the Redbrick portfolio.
What Shift can do for you:
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Apache Flink
Apache Flink is a robust framework and distributed processing engine designed for executing stateful computations on both continuous and finite data streams. It has been specifically developed to function effortlessly across different cluster settings, providing computations with remarkable in-memory speed and the ability to scale. Data in various forms is produced as a steady stream of events, which includes credit card transactions, sensor readings, machine logs, and user activities on websites or mobile applications. The strengths of Apache Flink become especially apparent in its ability to manage both unbounded and bounded data sets effectively. Its sophisticated handling of time and state enables Flink's runtime to cater to a diverse array of applications that work with unbounded streams. When it comes to bounded streams, Flink utilizes tailored algorithms and data structures that are optimized for fixed-size data collections, ensuring exceptional performance. In addition, Flink's capability to integrate with various resource managers adds to its adaptability across different computing platforms. As a result, Flink proves to be an invaluable resource for developers in pursuit of efficient and dependable solutions for stream processing, making it a go-to choice in the data engineering landscape.
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Apache Storm
Apache Storm is a robust open-source framework designed for distributed real-time computations, enabling the reliable handling of endless streams of data, much like how Hadoop transformed the landscape of batch processing. This platform boasts a user-friendly interface, supports multiple programming languages, and offers an enjoyable user experience. Its wide-ranging applications encompass real-time analytics, ongoing computations, online machine learning, distributed remote procedure calls, and the processes of extraction, transformation, and loading (ETL). Notably, performance tests indicate that Apache Storm can achieve processing speeds exceeding one million tuples per second per node, highlighting its remarkable efficiency. Furthermore, the system is built to be both scalable and fault-tolerant, guaranteeing uninterrupted data processing while remaining easy to install and manage. Apache Storm also integrates smoothly with existing queuing systems and various database technologies, enhancing its versatility. Within a typical setup, data streams are managed and processed through a topology capable of complex operations, which facilitates the flexible repartitioning of data at different computation stages. For further insights, a detailed tutorial is accessible online, making it an invaluable resource for users. Consequently, Apache Storm stands out as an exceptional option for organizations eager to harness the power of real-time data processing capabilities effectively.
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