Open Source TypeScript Data Management Systems - Page 2
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TypeScript Data Management Systems
View 4222 business solutionsBrowse free open source TypeScript Data Management Systems and projects below. Use the toggles on the left to filter open source TypeScript Data Management Systems by OS, license, language, programming language, and project status.
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Fully Managed MySQL, PostgreSQL, and SQL ServerCloud SQL handles your database ops end to end, so you can focus on your app.
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Superstruct
A simple and composable way to validate data in JavaScript
This project is a lightweight validation library for JavaScript and TypeScript that helps you define data “shapes” and validate runtime values against them. Instead of relying only on compile-time typing, it focuses on the reality that many apps receive unknown input from APIs, forms, and external systems, and those values need runtime checks. Its API is intentionally familiar if you’ve used TypeScript, Flow, Go structs, or GraphQL schemas, but the output is oriented around runtime correctness. When validation fails, it can throw or return detailed errors that are useful both for debugging and for communicating issues back to end users or API clients. The library is designed to be composable, so you can build larger validators from small pieces rather than rewriting similar checks in multiple places. It’s especially effective in REST or GraphQL servers, but it’s equally useful for protecting internal boundaries where untrusted or loosely typed data can slip in. -
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BizCharts
Powerful data visualization library based on G2 and React
BizCharts is Alibaba's general charting component library, dedicated to creating efficient, professional and convenient data visualization solutions in the middle and backend of enterprises. Based on the React charting library packaged by G2 and G2Plot, it has experienced three years of baptism in Alibaba's complex business scenarios. In terms of convenience, ease of use, and richness, it satisfies the business implementation of conventional charts and highly customized charts. After years of accumulation and continuous polishing, BizCharts 4.0 has been newly upgraded; in addition to having a flexible graphics syntax, it has added an interactive syntax and a better animation experience. At the same time, it enhances the React coding ability, and the writing is freer. The built-in encapsulation of responsive chart g2-plot works out of the box and complements the atomic capabilities of BizCharts to keep moving forward on the visual path of flexibility and ease of use. -
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Checkmate
Checkmate is an open-source, self-hosted tool
Checkmate is an open-source, self-hosted infrastructure monitoring platform that provides real-time visibility into server health, uptime, response times, and incident activity through a modern web interface. The application continuously checks whether websites and services are accessible and performing optimally, generating alerts and reports when availability or performance degrades. It supports detailed infrastructure monitoring through an optional agent called Capture, which collects hardware metrics such as CPU, memory, disk usage, and temperature from remote machines. The system is designed to scale, having been stress-tested with more than a thousand active monitors without major performance issues. Checkmate also includes incident tracking and notification capabilities so teams can quickly respond to outages or anomalies. Overall, the platform serves as a comprehensive, developer-friendly alternative to commercial uptime and infrastructure monitoring tools. -
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Neuroglancer
WebGL-based viewer for volumetric data
Neuroglancer is a WebGL-based visualization tool designed for exploring large-scale volumetric and neuroimaging datasets directly in the browser. It allows users to interactively view arbitrary 2D and 3D cross-sections of volumetric data alongside 3D meshes and skeleton models, enabling precise examination of neural structures and biological imaging results. Its multi-pane interface synchronizes multiple orthogonal views with a central 3D viewport, making it ideal for analyzing complex brain imaging data such as connectomics datasets. Neuroglancer operates entirely client-side, fetching data over HTTP in a variety of supported formats including Neuroglancer precomputed, N5, Zarr, and NIfTI, among others. The viewer is built with a multi-threaded architecture, separating rendering and data processing to ensure smooth performance even with massive datasets. Extensively used in neuroscience research, Neuroglancer supports integration with tools. -
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Outerbase
A lightweight Database GUI in your browser
Outerbase Studio is an open-source, browser-based database GUI designed for simplicity and versatility. It supports connecting to various relational databases, providing an intuitive interface for managing and querying data without the need for complex setups. -
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Querybook
Big Data Querying UI, combining collocated table metadata
Querybook is Pinterest’s open-source big data IDE via a notebook interface. Querybook’s core focus is to make composing queries, creating analyses, and collaborating with others as simple as possible. Organize rich text, queries, and charts into a notebook to easily document your analyses. Work collaboratively with others in a DataDoc and get real-time updates. The Query Editor is aware of your tables and their columns, as such it provides autocompletion, syntax highlighting, and the ability to hover or click on a table to view its information. No need to leave Querybook to create charts to quickly visualize your results. With a familiar interface easily create line, bar, stacked area, pie, horizontal bar, donut, scatter, and table charts. Add them then to your DataDoc to complete your data narrative. -
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tabix
Tabix.io UI
Open source simple business intelligence application and sql editor tool for Clickhouse. Auto-completion of fields, dictionaries and functions. Tips on fields and functions in Russian and English. Reformatting queries / autoformat. Minimizes brackets and subqueries. Setting the autocompletion / enableLiveAutocompletion. Backlight brackets. The list of functions is loaded based on the capabilities of the server. Displays which query is running. Display the number of tables at the database. The icon of the table depends on its engine. List of fields in the table and inserting the field when clicking in the editor. DB selection via double click in the tree, pop-up window about selection. Search in the tree of objects, filtering the tree. Rebuilding the list of databases / tables after the query is executed. Table with information about completed requests at the end of the list / Requests in the tab are logged for performance comparison. -
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Davinci
Davinci is a DVsaaS (Data Visualization as a Service) Platform
Davinci is oriented towards product managers, business people, data engineers, data analysts, data scientists, etc. It aims to provide a one-stop data visualization solution, which could be both independently used as a public cloud/private cloud and integrated into third-party systems as plugin. A simple configuration on Davinci UI can meet multiple visualization requirements. It also supports other visualization features like advanced interaction, industry analysis, pattern searching, social intelligence, etc. Sharing and intelligence capability means users could share their dashboards with others, which stimulates them to improve the visualization ability both in aesthetic perception and technical skills. In the field of data visualization, Davinci attaches great importance to basic interaction ability and various chart options; meanwhile, it lays more stress on integration and customization capability as well as sharing and intelligence capability. -
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Hedgehog Lab
Run, compile and execute JavaScript for Scientific Computing
Hedgehog Lab is an open-source scientific computation tool in the browser. Before the development, Pleases make sure you are already installed and enabled the yarn. Once cloned, switch to the dev branch and navigate to the folder by typing cd hedgehog-lab and then running the provided commands. On each run the program compiles and it takes time. Please wait until it shows "Compiled successfully!" and instructions about with which IP:PORT to connect. -
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React Chart.js
React components for Chart.js, the most popular charting library
React components for Chart.js, the most popular charting library. With v4, this library introduces a number of breaking changes. In order to improve performance, offer new features, and improve maintainability, it was necessary to break backwards compatibility, but we aimed to do so only when worth the benefit. You will find that any event which causes the chart to re-render, such as hover tooltips, etc., will cause the first dataset to be copied over to other datasets, causing your lines and bars to merge together. This is because to track changes in the dataset series, the library needs a key to be specified. If none is found, it can't tell the difference between the datasets while updating. Specify a different property to be used as a key by passing a datasetIdKey prop to your chart component. -
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immutability-helper
Mutate a copy of data without changing the original source
React lets you use whatever style of data management you want, including mutation. However, if you can use immutable data in performance-critical parts of your application it's easy to implement a fast shouldComponentUpdate() method to significantly speed up your app. Dealing with immutable data in JavaScript is more difficult than in languages designed for it, like Clojure. However, we've provided a simple immutability helper, update(), that makes dealing with this type of data much easier, without fundamentally changing how your data is represented. You can also take a look at Facebook's Immutable.js and React’s Using Immutable Data Structures section for more detail on Immutable.js. You have no way of determining which data has changed since the previous copy has been overwritten. Instead, you need to create a new copy of myData and change only the parts of it that need to be changed. -
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nw_wrld
nw_wrld is an event-driven sequencer for triggering visuals
nw_wrld is a procedurally generated world-building engine tailored for game developers and interactive storytellers who want to craft rich, random yet coherent environments without hand-crafting every detail. It uses noise functions and modular terrain algorithms to generate expansive maps, diverse biomes, and layered features like rivers, mountain ranges, forests, and resource nodes. The system is designed to be extensible, letting developers plug in new generation rules or tweak parameters with real-time previews so they can iterate rapidly on world design. It also includes utilities to derive metadata from worlds, such as climate distributions, strategic points of interest, and navigable paths, which can be consumed by gameplay systems or AI agents. For teams building games or simulations, nw_wrld provides a reusable foundation that reduces upfront world design costs while enabling endless variety. -
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Graffle
Simple GraphQL Client for JavaScript
Graffle is a simple, minimal, and extensible GraphQL client for JavaScript, designed to provide type-safe queries and run in various environments. -
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re_data
re_data - fix data issues before your users & CEO would discover them
re_data is an open-source data reliability framework for the modern data stack. Currently, re_data focuses on observing the dbt project (together with underlying data warehouse - Postgres, BigQuery, Snowflake, Redshift). Gather all relevant outputs about your data in one place using our cloud. Invite your team and debug it easily from there. Go back in time, and see your past metadata. Set up Slack notifications to always know when a new report is produced or an existing one got updated. -
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D-Tale
Visualizer for pandas data structures
D-Tale is the combination of a Flask backend and a React front-end to bring you an easy way to view & analyze Pandas data structures. It integrates seamlessly with ipython notebooks & python/ipython terminals. Currently, this tool supports such Pandas objects as DataFrame, Series, MultiIndex, DatetimeIndex & RangeIndex. D-Tale was the product of a SAS to Python conversion. What was originally a perl script wrapper on top of SAS's insight function is now a lightweight web client on top of Pandas data structures. To help guard against users loading the same data to D-Tale multiple times and thus eating up precious memory, we have a loose check for duplicate input data. If you are running ipython<=5.0 then you also have the ability to adjust the size of your output cell for the most recent instance displayed. JupyterHub has an extension that allows to proxy port for user, JupyterHub Server Proxy. -
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Vue Clock Visualizer
Simple clock component written in Vue
Simple clock component is written in Vue. -
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arcgis-rest-js
compact, modular JavaScript wrappers for the ArcGIS REST API
Compact, modular JavaScript wrappers for the ArcGIS REST API that run in Node.js and modern browsers. ArcGIS REST JS is supported in Node.js 8.x and above. It requires additional packages to polyfill Fetch and FormData. ArcGIS REST JS is supported in the same browsers as the ArcGIS API for JavaScript. ArcGIS REST JS takes advantage of web standards that are supported in all modern desktop browsers and most mobile browsers. ArcGIS REST JS can be deployed with a variety of build tools. -
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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. -
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Briefer
Dashboards and notebooks in a single place
Briefer is an open-source collaborative data platform that brings notebooks, dashboards, and interactive data apps into a unified workspace that combines the flexibility of code with the simplicity of visual exploration. It’s designed so technical users can write Markdown, SQL, and Python side by side for data analysis, visualization, and reporting, while non-technical viewers can interact with results through inputs, dropdowns, and date pickers without writing any code. Users work in a Notion-style interface where they can build, organize, and share pages that contain executable code blocks, charts, text explanations, and interactive elements within the same document, enabling rich data storytelling and reproducible analytics. Briefer supports real-time collaboration, meaning multiple teammates can edit the same notebook or dashboard simultaneously and see changes live, which encourages shared analysis and decision making. -
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DataStation Community Edition
App to easily query, script, and visualize data from every database
DataStation is an open-source data IDE for developers. It allows you to easily build graphs and tables with data pulled from SQL databases, logging databases, metrics databases, HTTP servers, and all kinds of text and binary files. Need to join or munge data? Write embedded scripts as needed in languages like Python, JavaScript, R or SQL. All in one application. Build reports with graphs, charts and tables. Script against data. Cross-platform: Windows, macOS, and Linux. Easily fetch your data, wherever it is: 18 SQL and non-SQL databases, files, HTTP server. Over 20 supported databases out of the box including: PostgreSQL, MySQL, MariaDB, SQLite, SQL Server, Oracle, ClickHouse, Influx 1 (InfluxQL), Influx 2 (Flux), Prometheus, Elasticsearch, AWS Athena, Google BigQuery, Snowflake, Cassandra, Scylla, TimescaleDB, YugabyteDB, CockroachDB, CrateDB, QuestDB, and Airtable. -
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Durable Streams
The open protocol for real-time sync to client applications
Durable Streams is an open protocol and reference implementation designed to standardize reliable, resumable, real-time streaming between servers and client applications using simple HTTP semantics, filling a gap left by ephemeral technologies like WebSockets and traditional SSE. It defines an append-only, offset-addressable stream primitive where each stream is mapped to a URL that clients can read from or tail, supporting catch-up reads, historical replay, and live updates with robust resume capabilities across reconnections. The protocol is aimed at modern client-centric applications including AI token streaming, mobile and web UI sync, collaborative editing, and other real-time scenarios where network interruptions are common and clients must maintain continuity. -
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EDIBridge
Walmart EDI compliance in 15 minutes $49/month
EDIBridge is now in Beta. It ships with a Walmart Supplier Package that lets small suppliers install a full EDI setup in a guided 6-step wizard and go live in ~15 minutes. AI auto-maps CSV/Excel fields to 850 PO, 856 ASN, 810 Invoice & 997 ACK. Includes AS2 + SFTP delivery and a visual drag-and-drop mapper. No EDI expertise required. Flat $49/month with zero per-transaction fees. First 20 sign-ups get 3 months free after their initial paid month. Target & Amazon packages coming soon. -
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Facets
Visualizations for machine learning datasets
The power of machine learning comes from its ability to learn patterns from large amounts of data. Understanding your data is critical to building a powerful machine learning system. Facets contains two robust visualizations to aid in understanding and analyzing machine learning datasets. Get a sense of the shape of each feature of your dataset using Facets Overview, or explore individual observations using Facets Dive. Explore Facets Overview and Facets Dive on the UCI Census Income dataset, used for predicting whether an individual’s income exceeds $50K/yr based on their census data. The census data contains features such as age, education level, and occupation for each individual. Overview gives users a quick understanding of the distribution of values across the features of their dataset(s). Uncover several uncommon and common issues such as unexpected feature values, missing feature values for a large number of observation, training/serving skew and train/test/validation set skew. -
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HiPlot
HiPlot makes understanding high dimensional data easy
HiPlot is an interactive visualization toolkit for exploring high-dimensional experiments, especially those produced during hyperparameter search or ablation studies. Its core view is a parallel-coordinates plot that lets you brush, filter, and highlight runs to spot trade-offs, correlations, and Pareto fronts at a glance. You can load results from simple CSV/JSON logs or programmatically push “experiments” with typed fields, metrics, and tags. The UI supports dynamic filtering, color mapping, and tooltip details so you can iteratively narrow to the most promising configurations. Because it renders as self-contained HTML, you can embed the visualization in notebooks, export it, or serve it as a lightweight web app for teammates. HiPlot also offers summary statistics, correlation hints, and outlier highlighting to surface patterns that aren’t obvious from raw tables. -
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Jitsu
Jitsu is an open-source Segment alternative
Jitsu is a fully-scriptable data ingestion engine for modern data teams. Set-up a real-time data pipeline in minutes, not days. Installing Jitsu is a matter of selecting your framework and adding few lines of code to your app. Jitsu is built to be framework agnostic, so regardless of your stack, we have a solution that'll work for your team. Connect data warehouse (Snowflake, Clickhouse, BigQuery, S3, Redshift ot Postgres) and query your data instantly. Jitsu can either stream data in real-time or send it in micro-batches (up to once a minute). Apply any transformation with Jitsu. Just write JavaScript code right in the UI to do anything with incoming data. And yes, the code editor supports code completion, debugging and many more. It feels like a full-featured IDE!
