The global in-memory database market size was valued at USD 10.5643 billion in 2025 and is projected to grow at a compound annual growth rate (CAGR) of 16.19% during the forecast period (2025-2033). The growth of the market is attributed to the increasing adoption of in-memory databases in various industries to improve data processing speed and performance. In-memory databases store data in the computer's main memory (RAM) instead of on a physical disk, which allows for faster data access and retrieval. Key market drivers include the growing volume of data, the need for real-time data analysis, and the increasing adoption of cloud computing. The growing volume of data, often referred to as "big data," is a significant factor driving market growth. The need for real-time data analysis is another key driver, as in-memory databases can provide faster data access than traditional databases. The increasing adoption of cloud computing is also driving market growth, as cloud-based in-memory databases offer scalability and flexibility. Recent developments include: March 2023: SAP revealed SAP Datasphere, the company's next-gen data management system. It gives customers easy access to business-ready data across the data landscape. SAP also announced strategic agreements with top data and AI companies, including Collibra NV, Confluent Inc., Databricks Inc., and DataRobot Inc., to improve SAP Datasphere and allow organizations to build a unified data architecture that securely combines SAP software data and non-SAP data., June 2023: IBM has released a new tool to aid corporations in monitoring their carbon footprint pollution across cloud services and improve their sustainability as they move to hybrid and multi-cloud environments. The IBM Cloud Carbon Calculator, an AI-powered dashboard, is now available to everyone. It can help clients access emissions data for various IBM Cloud tasks, such as AI, high-performance computing (HPC), and financial services., SingleStoreDB for December 2022 was announced last year by IBM and SingleStore. With IBM introducing SingleStoreDB as a solution, businesses are now moving forward in their strategic relationship to deliver the quickest, most scalable data platform that supports data-intensive programs. For Azure, AWS, and Microsoft Azure marketplace, IBM has released SingleStoreDB as a service., In April 2022, McObject issued the eXtremeDB/rt database management system (DBMS) for Green Hills Software’s Integrity RTOS. The first-ever commercial off-the-shelf (COTS) real-time DBMS satisfying basic criteria of temporal and deterministic consistency in data is known as eXtremeDB/rt. It was initially conceived and built as an integrated in-memory database system for embedded systems., November 2022: Redis, provider of real-time in-memory databases, and Amazon Web Services have formed a multi-year strategic alliance. It is a networked open-source NoSQL system that stores data on disk for durability before moving it to DRAM as required. As such, it can be used as a message broker cache, streaming engine, or database., December 2022: The largest Indian stock exchange, National Stock Exchange, opted for Raima Database Manager (RDM) Workgroup 12.0 In-Memory System as its foundational component for upcoming versions of its trading platform front-end called National Exchange for Automated Trading (NEAT)., On January 13th, 2021, Oracle launched Oracle Database 21c – the latest version of the world’s leading converged database available on Oracle Cloud with the Always Free tier of Oracle Autonomous Database included. It includes more than two hundred new features, according to Oracle’s press release, including immutable blockchain tables; In-Database JavaScript; native JSON binary data type; AutoML for in-database machine learning (ML); persistent memory store; enhancements, including improvements regarding graph processing performance that support sharding, multitenant, and security., Stanford engineers have developed a new chip to increase the efficiency of AI computing in August 2022. Stanford engineers have created a more efficient and flexible AI chip that could bring the power of AI into tiny edge devices., In-Memory Database Market Segmentation,

Relational

NoSQL

NewSQL

,

Online Analytical Processing (OLAP)

Online Transaction Processing (OLTP)

,

Transaction

Reporting

Analytics

,

North America

US

Canada

Europe

Germany

France

UK

Italy

Spain

Rest of Europe

Asia-Pacific

China

Japan

India

Australia

South Korea

Australia

Rest of Asia-Pacific

Rest of the World

Middle East

Africa

Latin America

, . Potential restraints include: Security And Data Privacy Concerns 26.

Visit >>> Frontend Masters - Build a Fullstack App with Vanilla JS and Go Course details Build a Full-Stack Real-World Web Application from Scratch In this three-day workshop, you will build a real-world, fully functional web application from scratch using Vanilla JavaScript for the frontend and Go for the backend. You’ll follow industry best practices for structuring a full-stack project, working with APIs, handling authentication, managing state, and securing data. By the end of the workshop, you’ll have a complete, production-ready application ready to deploy and scale. Key Takeaways By participating along with us in the workshop, you ll learn: - Develop a real-world full-stack application from scratch - Master best practices for frontend and backend development - Learn how to create and consume APIs with Go and JavaScript without a framework - Implement authentication, state management, and data sync -

This dataset contains contract award data from the Federal Procurement Data System Next-Generation (FPDS-NG) for fiscal years 2014 through 2020. The primary data consists of 3,992,467 observations, after undersampling, of contract descriptions as well as related Product and Service Codes (PSCs). The secondary data consists of dictionary information on the PSCs and related spend categories. Data is in JavaScript Object Notation (JSON) as a JSON-API v1.0 compound document.

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Web Development Market Size 2025-2029

The web development market size is forecast to increase by USD 40.98 billion at a CAGR of 10.4% between 2024 and 2029.

The market is experiencing significant growth, driven by the increasing digital transformation across industries and the integration of artificial intelligence (AI) into web applications. This trend is fueled by the need for businesses to enhance user experience, streamline operations, and gain a competitive edge in the market. Furthermore, the rapid evolution of technologies such as Progressive Web Apps (PWAs), serverless architecture, and the Internet of Things (IoT) is creating new opportunities for innovation and expansion. However, this market is not without challenges. The ever-changing technological landscape requires web developers to continuously update their skills and knowledge. Additionally, ensuring web applications are secure and compliant with data protection regulations is becoming increasingly complex.
Companies seeking to capitalize on market opportunities and navigate challenges effectively should focus on building a team of skilled developers, investing in continuous learning and development, and prioritizing security and compliance in their web development projects. By staying abreast of the latest trends and technologies, and adapting quickly to market shifts, organizations can successfully navigate the dynamic the market and drive business growth.

What will be the Size of the Web Development Market during the forecast period?

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The market continues to evolve at an unprecedented pace, driven by advancements in technology and shifting consumer preferences. Key trends include the adoption of Agile methodologies, DevOps tools, and version control systems for streamlined project management. JavaScript frameworks, such as React and Angular, dominate front-end development, while Magento, Shopify, and WordPress lead in content management and e-commerce. Back-end development sees a rise in Python, PHP, and Ruby on Rails frameworks, enabling faster development and more efficient scalability. Interaction design, user-centered design, and mobile-first design prioritize user experience, while security audits, penetration testing, and disaster recovery solutions ensure website safety.
Marketing automation, email marketing platforms, and CRM systems enhance digital marketing efforts, while social media analytics and Google Analytics provide valuable insights for data-driven decision-making. Progressive enhancement, headless CMS, and cloud migration further expand the market's potential. Overall, the market remains a dynamic, innovative space, with continuous growth fueled by evolving business needs and technological advancements.

How is this Web Development Industry segmented?

The web development industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

End-user

  Retail and e-commerce
  BFSI
  IT and telecom
  Healthcare
  Others


Business Segment

  SMEs
  Large enterprise


Service Type

  Front-End Development
  Back-End Development
  Full-Stack Development
  E-Commerce Development


Deployment Type

  Cloud-Based
  On-Premises


Technology Specificity

  JavaScript
  Python
  PHP
  Ruby


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Spain
    UK


  APAC

    China
    India
    Japan


  South America

    Brazil


  Rest of World (ROW)

By End-user Insights

The retail and e-commerce segment is estimated to witness significant growth during the forecast period. The market is experiencing significant growth due to the digital transformation sweeping various industries. E-commerce and retail sectors lead the market, driven by the increasing preference for online shopping and improved Internet penetration. To cater to this trend, businesses demand user-engaging web applications with smooth navigation, secure payment gateways, and seamless product search and purchase features. Mobile shopping's rise necessitates mobile app development and mobile-optimized websites. Agile development, microservices architecture, and UI/UX design are essential elements in creating engaging and efficient web solutions. Furthermore, AI, machine learning, and data analytics enable data-driven decision making, customer loyalty, and business intelligence.

Web hosting, cloud computing, API integration, and growth hacking are other critical components. Ensuring web accessibility, data security, and e-commerce development is also crucial for businesses in the digital age. Online advertising, email marketing, content strategy, brand building, and data visualization are essential aspects of digital marketing. Serverless computin

We present GHTraffic, a dataset of significant size comprising HTTP transactions extracted from GitHub data (i.e., from 04 August 2015 GHTorrent issues snapshot) and augmented with synthetic transaction data. This dataset facilitates reproducible research on many aspects of service-oriented computing.

The GHTraffic dataset comprises three different editions: Small (S), Medium (M) and Large (L). The S dataset includes HTTP transaction records created from google/guava repository. Guava is a popular Java library containing utilities and data structures. The M dataset includes records from the npm/npm project. It is the popular de-facto standard package manager for JavaScript. The L dataset contains data that were created by selecting eight repositories containing large and very active projects, including twbs/bootstrap, symfony/symfony, docker/docker, Homebrew/homebrew, rust-lang/rust, kubernetes/kubernetes, rails/rails, and angular/angular.js.

We also provide access to the scripts used to generate GHTraffic. Using these scripts, users can modify the configuration properties in the config.properties file in order to create a customised version of GHTraffic datasets for their own use. The readme.md file included in the distribution provides further information on how to build the code and run the scripts.

The GHTraffic scripts can be accessed by downloading the pre-configured VirtualBox image or by cloning the repository.

THIS RESOURCE IS NO LONGER IN SERVICE. Documented August 23, 2017.A web based central repository for individual and group analysis of Arterial Spin Labeling (ASL) data sets and ASL pulse sequences developed at CMFRI UCSD for MRI researchers. This resource currently hosts more 1300 ASL data sets from 22 projects and consists of mainly two main tools 1) The Cerebral Blood Flow Database and Analysis Pipeline (CBFDAP) is a web enabled data and workflow management system extended from the HID codebase on NITRC specialized for Arterial Spin Labeling data management and analysis (including group analysis) in a centralized manner. 2) Pulse Sequence Distribution System (PSDS) for managing dissamination of ASL pulse sequences developed at the UCSD CFMRI. This resource also includes web and video tutorials for end users.

We present the data collected as part of the Open-source Complex Ecosystem And Networks (OCEAN) partnership between Google Open Source and the University of Vermont. This includes mailing list emails with standardized format spanning the past three decades from fourteen mailing lists across four different open source communities: Python, Angular, Node.js, and the Go language.This data is presented in the following publication: Warrick, M., Rosenblatt, S. F., Young, J. G., Casari, A., Hébert-Dufresne, L., & Bagrow, J. P. (2022). The OCEAN mailing list data set: Network analysis spanning mailing lists and code repositories. In 2022 IEEE/ACM 19th International Conference on Mining Software Repositories (MSR). IEEE.

This dataset contains the data platform for the research project "OwnReality. To Each His Own Reality". During the course of the project, data was gathered and entered into a database. In general, this platform allows the integration of that data into web based systems such as content management systems. To be independent of the target technology, the integration is implemented with a set of customized html tags with no assumptions on lower layers. An API-only web application retrieves the data from an elasticsearch instance and relays to the widgets. A README in this dataset serves as documentation. It aims to provide information on: the requirements to run the application how to set up the API-application importing the data from the included json documents importing the additional image data building the javascript integration asset how to integrate the widgets on a third-party page Requirements linux (not a requirement but the howto in documentation assumes linux) elasticsearch (2.2.3) ruby (2.2.5) nodejs (4.4.4), only for building

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Notes for selected categories: Interface: General impression of the interface style. Interactive GUI = GUI as in contemporary user-friendly applications such as MS Word. Tabular = output is presented mostly as tables, possible with some limited interaction (sorting by table columns). Integrated BLAST: whether the program supports BLAST searches started from within the program. Multi-query analysis: whether multiple queries can be visualized and analysed in an integrated way. Graphical alignments: how alignments between queries and hits are graphically displayed. Query-hits = one selected query is displayed with the associated hits. Hit-Queries = one selected hit is displayed with its associated queries. High-throughput: whether the program can handle high-throughput BLAST data, i.e. BLAST results with more than 10 000 queries. Splitting and merging files: whether it is possible to split files (and possible merge them subsequently) to handle large data set. Additional features: Program features extending the information originally present in the BLAST output file. BLAST+ compatible: The latest NCBI BLAST implementation (denominated BLAST+) includes a changed BLAST output format. N/A = Not Applicable. (XLSX)

Introduction to the intellectual enterprises of computer science and the art of programming. This course teaches students how to think algorithmically and solve problems efficiently. Topics include abstraction, algorithms, encapsulation, data structures, databases, memory management, security, software development, virtualization, and websites. Languages include C, PHP, and JavaScript plus SQL, CSS, and HTML. Problem sets inspired by real-world domains of biology, cryptography, finance, forensics, and gaming. Designed for concentrators and non-concentrators alike, with or without prior programming experience.

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Online clearance system is a research work that will help build an effective information management for schools. It is aimed at developing a system for making clearance after graduation . The designed software will serve as a more reliable and effective means of undertaking students clearance, remove all forms of delay and stress as well as enable you understand the procedures involved as well as how to do your clearance online. This project work made use of data collected from the University, materials and journals from various authors and software was developed to effectively achieve the aims of this project. In this project, the implementation of the computer-based system was carried out using PHP, JAVASCRIPT, CSS, APACHE and MYSQL for the database. In conclusion, the work met all the objectives intended. It is, however, recommended for use by all tertiary institutions.

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