Best Data Management Software for TypeScript

In just a few days, you can integrate and customize a lightning-fast financial table with your product. You can make changes or create a completely new interface. You want more? We offer a full access alternative. Data feeds with futures and indices, equities, FX and cryptocurrencies by default. Sign up now to get your data feeds. DXcharts can be integrated with any market data source, as it is data feed-agnostic. Native libraries for all platforms. Native web, native mobile & desktop. Get a solution that is specifically tailored to your product. Analyzing statistics from trading activity can help you evaluate securities and predict their future movements. You can create custom studies with the intuitive dxScript. You can adjust the layout of charts however you like and sync them by instrument, chart type and timeframe, range, studies & appearance.

Recognized worldwide for excellence, AnyChart is an award-winning JavaScript (HTML5) library that empowers teams to transform raw data into engaging visual experiences. Built to serve the needs of both developers and businesses, it provides a complete toolkit for creating interactive charts, maps, and dashboards that perform reliably across web, mobile, and desktop environments. With a robust set of over 90 chart types — including Gantt, stock, geospatial, bar, and line — AnyChart makes it easy to turn complex information into clear, actionable insights. Its seamless integration with any technology stack and compatibility with diverse data sources make it ideal for enhancing reports, powering embedded analytics in SaaS platforms, or supporting enterprise-grade systems. Fully customizable, responsive, and continuously evolving with new features, AnyChart delivers simplicity, flexibility, and fast, high-quality results. Trusted by more than 75% of Fortune 500 companies and thousands of developers all over the world, it is the proven choice for advanced data visualization. Get started with AnyChart JS Charts today!

One Platform for Realtime Communication: A platform to build and operate real-time interactivity for web, mobile, AI/ML, IoT, and Edge computing applications Faster & Easier Deployments: SDK support for 50+ mobile, web, server, and IoT environments (PubNub & community supported) and more than 65 pre-built integrations with external and third-party APIs to give you the features you need regardless of programming language or tech stack. Scalability: The industry’s most scalable platform capable of supporting millions of concurrent users for rapid growth with low latency, high uptime, and without financial penalties.

amCharts is a set of JavaScript libraries and tools for all your data visualization needs on the web. amCharts Charts supports classic charts like Line, Area, Column, Bar, Pie, XY, Scatter, Candlestick, Radar, Polar, and OHLC as well as more “exotic” ones like Gauges, Funnels, Gantt, Chord and Sankey diagrams, Force-Directed Trees, TreeMap, Sunburst Chart and more. amCharts Maps offers fully interactive adaptive world or local country maps and map charts. Additionally, amCharts provides a specialized Stock Chart tailored for visualization and analysis of stock and other time-based data. All products are available for free (with a small backlink) for any type of use, as well as in paid commercial form covering all kinds of usage scenarios.

Metal serves as a comprehensive, fully-managed machine learning retrieval platform ready for production. With Metal, you can uncover insights from your unstructured data by leveraging embeddings effectively. It operates as a managed service, enabling the development of AI products without the complications associated with infrastructure management. The platform supports various integrations, including OpenAI and CLIP, among others. You can efficiently process and segment your documents, maximizing the benefits of our system in live environments. The MetalRetriever can be easily integrated, and a straightforward /search endpoint facilitates running approximate nearest neighbor (ANN) queries. You can begin your journey with a free account, and Metal provides API keys for accessing our API and SDKs seamlessly. By using your API Key, you can authenticate by adjusting the headers accordingly. Our Typescript SDK is available to help you incorporate Metal into your application, although it's also compatible with JavaScript. There is a mechanism to programmatically fine-tune your specific machine learning model, and you also gain access to an indexed vector database containing your embeddings. Additionally, Metal offers resources tailored to represent your unique ML use-case, ensuring you have the tools needed for your specific requirements. Furthermore, this flexibility allows developers to adapt the service to various applications across different industries.

Utilize our extensive infrastructure, which includes global IPs, a comprehensive browser cluster, and advanced CAPTCHA solving technology, to access and leverage our organized SERP data however you choose. Each API call operates within a fully functional browser environment, and we take care of solving all CAPTCHAs, effectively replicating human behavior. This approach ensures that you receive the exact information as it appears to users. Serp Api employs Google’s geolocated, encrypted parameters and directs your request through the nearest proxy server to your specified location, thereby enhancing precision. Additionally, we offer a wealth of structured data for every result, featuring links, locations, tweets, prices, images, ratings, reviews, rich snippets, and much more, ensuring you have a comprehensive set of information at your fingertips. With this rich array of data, you can gain valuable insights into user behavior and preferences.

An AI-driven code scanning tool aims to adopt a proactive, shift-left approach for safeguarding sensitive information and ensuring compliance with privacy regulations. The rapid evolution of product development often surpasses the capacity of privacy teams, necessitating frequent updates to outdated data maps, which can significantly burden their workload. With HoundDog.ai’s advanced code scanner, vulnerabilities that traditional SAST scanners might miss can be continuously identified, especially those exposing sensitive data in plaintext through various channels like logs, files, tokens, cookies, or external systems. It provides critical insights and remediation techniques, such as the removal of sensitive data, implementation of masking or obfuscation, or substitution of PII with UUIDs. Users receive timely alerts when new data elements are added, categorized by their sensitivity levels, helping to prevent unauthorized product changes from being released, thus mitigating potential privacy breaches. By automating these processes, the scanner effectively reduces the reliance on manual methods, which are often riddled with errors. This innovative solution not only enhances security but also streamlines workflow for privacy teams, allowing them to focus on more strategic initiatives.

LanceDB is an accessible, open-source database specifically designed for AI development. It offers features such as hyperscalable vector search and sophisticated retrieval capabilities for Retrieval-Augmented Generation (RAG), along with support for streaming training data and the interactive analysis of extensive AI datasets, making it an ideal foundation for AI applications. The installation process takes only seconds, and it integrates effortlessly into your current data and AI toolchain. As an embedded database—similar to SQLite or DuckDB—LanceDB supports native object storage integration, allowing it to be deployed in various environments and efficiently scale to zero when inactive. Whether for quick prototyping or large-scale production, LanceDB provides exceptional speed for search, analytics, and training involving multimodal AI data. Notably, prominent AI companies have indexed vast numbers of vectors and extensive volumes of text, images, and videos at a significantly lower cost compared to other vector databases. Beyond mere embedding, it allows for filtering, selection, and streaming of training data directly from object storage, thereby ensuring optimal GPU utilization for enhanced performance. This versatility makes LanceDB a powerful tool in the evolving landscape of artificial intelligence.

Dragonfly serves as a seamless substitute for Redis, offering enhanced performance while reducing costs. It is specifically engineered to harness the capabilities of contemporary cloud infrastructure, catering to the data requirements of today’s applications, thereby liberating developers from the constraints posed by conventional in-memory data solutions. Legacy software cannot fully exploit the advantages of modern cloud technology. With its optimization for cloud environments, Dragonfly achieves an impressive 25 times more throughput and reduces snapshotting latency by 12 times compared to older in-memory data solutions like Redis, making it easier to provide the immediate responses that users demand. The traditional single-threaded architecture of Redis leads to high expenses when scaling workloads. In contrast, Dragonfly is significantly more efficient in both computation and memory usage, potentially reducing infrastructure expenses by up to 80%. Initially, Dragonfly scales vertically, only transitioning to clustering when absolutely necessary at a very high scale, which simplifies the operational framework and enhances system reliability. Consequently, developers can focus more on innovation rather than infrastructure management.

Scrapfly provides a comprehensive set of APIs aimed at simplifying the process of web data gathering for developers. Their web scraping API is designed to effectively extract content from web pages, adeptly managing obstacles such as anti-scraping technologies and the complexities of JavaScript rendering. The Extraction API employs advanced AI and large language models to analyze documents and retrieve structured information, while the screenshot API captures high-definition images of web pages. These tools are engineered to scale, guaranteeing both reliability and performance as data requirements increase. Additionally, Scrapfly offers extensive documentation, SDKs for Python and TypeScript, and connections with platforms like Zapier and Make, making it easy to integrate these solutions into a variety of workflows. Users can take advantage of these features to enhance their data collection processes significantly.

WatermelonDB is a cutting-edge reactive database framework tailored for the development of robust React and React Native applications that can efficiently scale from a few hundred to tens of thousands of records while maintaining high speed. It guarantees immediate app launches, regardless of the amount of data, incorporates lazy loading to fetch data only when necessary, and features offline-first capabilities along with synchronization with your own backend systems. This framework is designed to be multiplatform. Specifically optimized for React, it facilitates uncomplicated data integration into components and is framework-agnostic, allowing developers to use its JavaScript API in conjunction with various other UI frameworks. Built on a solid SQLite infrastructure, WatermelonDB offers static typing through Flow or TypeScript, while also providing optional reactivity via an RxJS API. It effectively tackles performance challenges in complex applications by deferring data loading until explicitly requested and executing all queries directly on SQLite in a dedicated native thread, which ensures that the majority of queries are resolved almost instantly. Additionally, this innovative framework supports seamless data management, making it a versatile choice for developers aiming to enhance the performance and responsiveness of their applications.

Substrate serves as the foundation for agentic AI, featuring sophisticated abstractions and high-performance elements, including optimized models, a vector database, a code interpreter, and a model router. It stands out as the sole compute engine crafted specifically to handle complex multi-step AI tasks. By merely describing your task and linking components, Substrate can execute it at remarkable speed. Your workload is assessed as a directed acyclic graph, which is then optimized; for instance, it consolidates nodes that are suitable for batch processing. The Substrate inference engine efficiently organizes your workflow graph, employing enhanced parallelism to simplify the process of integrating various inference APIs. Forget about asynchronous programming—just connect the nodes and allow Substrate to handle the parallelization of your workload seamlessly. Our robust infrastructure ensures that your entire workload operates within the same cluster, often utilizing a single machine, thereby eliminating delays caused by unnecessary data transfers and cross-region HTTP requests. This streamlined approach not only enhances efficiency but also significantly accelerates task execution times.

Creating a robust data layer for contemporary applications is essential. Prisma serves as an alternative to conventional ORMs, offering a more straightforward and type-safe approach to database interactions. With its declarative migrations and data modeling features, it enhances the development process. The platform also provides powerful visual tools for managing data effectively. An automatically generated and type-safe database client streamlines the database access process. This client allows developers to interact with their databases effortlessly using the programming languages they prefer. Moreover, Prisma simplifies the implementation of GraphQL servers, enabling seamless integration. Understanding how to utilize the Prisma client within your resolvers is crucial for efficient database access. By leveraging these capabilities, developers can build applications that are both powerful and maintainable.

ExoCoding, an online platform for code generation, empowers software developers by enabling them to create better software faster. It uses AI-powered assistants that are based on models to generate boilerplate codes and streamline repetitive tasks. Developers can create applications that contain modules for Database Management, Logic Building and Interface Design. There are more features, such as sharing prototypes, task-planning, and a marketplace that offers pre-built templates, which enhance the developer experience. After generating the code (backend or frontend), it's business as usual. The same IDE, and other dev tool are used.

We provide an accessible platform designed to empower businesses across diverse sectors to undergo digital transformation and achieve enhanced insights that foster a lasting competitive edge. Our software suite features Contxt, a robust, real-time industrial platform functioning as the core data engine, along with Nsight, our application for data integration and intelligent analytics. Throughout this journey, we ensure comprehensive support and services. At the heart of our offering lies Contxt, our adaptable data management engine focused on industrial optimization. This platform is built upon our cutting-edge ETLT technology, which facilitates data availability in under 15 seconds for any transaction across various disconnected data sources. Contxt enables developers to construct a real-time digital twin, providing live data across all applications and analyses within the organization, thereby driving significant business outcomes. Ultimately, our commitment is to equip businesses with the tools they need to thrive in an increasingly competitive landscape.

Utilize the internet as though it were your personal API, engaging with leading websites without the hassle of fragile and complicated automation scripts. The web action SDK serves as a robust tool that enables you to programmatically interact with a variety of online platforms. By employing this SDK, you can automate processes, access data, and execute actions on well-known sites as if navigating through a web browser. You can connect with different platforms such as LinkedIn, Amazon, Uber, and Resy seamlessly. It integrates effortlessly into your current Node.js or TypeScript projects, enhancing your development workflow. Designed with TypeScript, it provides an improved developer experience and ensures code dependability. You can carry out a diverse array of operations, from searching for products to making bookings. Each platform comes with its exclusive set of functions; for instance, on LinkedIn, you have the ability to send messages, search for users, and manage your connections effectively. This SDK not only simplifies web interactions but also empowers developers to focus on building innovative applications.

Data contracts play a crucial role in enhancing the interaction between data teams and developers. Rather than merely identifying issues after they arise, it’s essential to proactively prevent them at the application level. Utilize AI-powered asset registration to monitor every alteration from all data sources. Amplify the success of data initiatives by ensuring visibility upstream and conducting thorough impact analyses. By implementing data governance as code and data contracts, both data ownership and management can be shifted left. Establishing trust in data is also vital, achieved through prompt communication regarding data quality standards and any modifications. Our AI-driven technology allows for the elimination of data problems right at their origin, ensuring a smoother workflow. Gable serves as a B2B data infrastructure SaaS that provides a collaborative platform specifically designed for the creation and enforcement of data contracts. These ‘data contracts’ are essentially API-based agreements between software engineers managing upstream data sources and the data engineers or analysts who utilize that data for machine learning model development and analytics. With Gable, organizations can streamline their data processes, ultimately fostering a culture of trust and efficiency.

Sequelize serves as a contemporary ORM for Node.js and TypeScript, compatible with various databases including Oracle, Postgres, MySQL, MariaDB, SQLite, and SQL Server. It boasts robust features such as transaction support, model relationships, eager and lazy loading, and read replication. Users can easily define models and optionally utilize automatic synchronization with the database. By establishing associations between models, it allows Sequelize to manage complex operations seamlessly. Instead of permanently deleting records, it offers the option to mark them as deleted. Additionally, features like transactions, migrations, strong typing, JSON querying, and lifecycle events (hooks) enhance its functionality. As a promise-based ORM, Sequelize facilitates connections to popular databases such as Amazon Redshift and Snowflake’s Data Cloud, requiring the creation of a Sequelize instance to initiate the connection process. Moreover, its flexibility makes it an excellent choice for developers looking to streamline database interactions efficiently.