Document Database Platform Market Outlook

According to our latest research, the Global Document Database Platform market size was valued at $7.8 billion in 2024 and is projected to reach $26.4 billion by 2033, expanding at a CAGR of 14.5% during the forecast period of 2025–2033. The primary driver behind this robust growth is the exponential surge in unstructured data generation across various industries, which has significantly increased the need for scalable, flexible, and high-performance document database platforms. As enterprises transition to digital-first operations and cloud-native architectures, document database platforms are becoming critical for efficient data management, real-time analytics, and seamless integration with next-generation applications. This market is further propelled by the increasing adoption of artificial intelligence and machine learning technologies, which demand sophisticated data storage and retrieval solutions capable of handling diverse and complex data types.

Regional Outlook

North America holds the largest share of the global Document Database Platform market, accounting for nearly 39% of the total market value in 2024. This dominance stems from the region’s mature IT infrastructure, high cloud adoption rates, and a strong presence of leading technology vendors such as MongoDB, Amazon Web Services, and Microsoft. The United States, in particular, has seen a rapid uptake of document database platforms in sectors like BFSI, healthcare, and retail, driven by stringent regulatory compliance requirements and the need for robust data security. Furthermore, North America’s innovation ecosystem, characterized by substantial investments in R&D and a vibrant startup culture, continues to foster advancements in database technologies, ensuring sustained market leadership throughout the forecast period.

In contrast, the Asia Pacific region is projected to be the fastest-growing market for document database platforms, with a forecasted CAGR of 17.2% from 2025 to 2033. The surge in digital transformation initiatives across countries such as China, India, and Japan is fueling unprecedented demand for scalable data management solutions. Rapid urbanization, the proliferation of e-commerce, and the expansion of fintech and healthcare sectors are key contributors to this growth. Governments in the region are actively promoting digital infrastructure development, which, coupled with increasing investments from global cloud service providers, is accelerating the adoption of document database platforms. Notably, the region’s large population base and growing internet penetration present significant opportunities for market expansion, particularly among small and medium enterprises seeking cost-effective and agile database solutions.

Emerging economies in Latin America and the Middle East & Africa are also witnessing gradual adoption of document database platforms, albeit at a slower pace compared to mature markets. Localized challenges such as limited access to advanced IT infrastructure, budget constraints, and data sovereignty concerns hinder widespread implementation. However, increasing awareness about the benefits of cloud-based database solutions and supportive government policies aimed at digitalization are gradually mitigating these barriers. In Latin America, countries like Brazil and Mexico are experiencing a rise in demand from the retail and government sectors, while in the Middle East & Africa, the focus is on leveraging document databases for smart city initiatives and enhancing public sector efficiency.

Report Scope

The Master Address Repository (MAR) 2.0 is the successor to the Master Address Repository. The Master Address Repository is a complex and widely accessed database that is increasingly being accessed by many DC Government applications. It is important to have high quality documentation readily accessible for such widely used databases. This document contains the column (field) definitions for the most important views, tables and feature classes within the MAR 2.0.

Completed data entry forms on SADME databases for directory being compiled by the BMR. Completed data entry forms on SADME databases for directory being compiled by the BMR.

This is a dataset download, not a document. The Open button will start the download.This data layer is an element of the Oregon GIS Framework. The Oregon Biodiversity Information Center (ORBIC), part of the Institute for Natural Resources (INR) within the Oregon University System, has been the steward of Oregon’s protected areas data since 1989. This data is incorporated into the NavigatOR GIS utility and the national US protected areas database maintained by the U.S. Geological Survey. New data in Oregon on conservation easements and newly developed protected area maps from local land trusts and County and City governments were incorporated in 2011-2013. The result is a very comprehensive map and protected areas database for Oregon. Updates and edits will continue to be made to improve the dataset.

A look up table of each subject matter a lobbyist can select to categorize their municipal question. You can recreate the City Clerk's lobbyist database by downloading all lobbyist datasets on the data portal and view the complete data model of the lobbyist database here: https://www.austintexas.gov/edims/document.cfm?id=293053

This table lists the clients reported by lobbyists. You can recreate the City Clerk's lobbyist database by downloading all lobbyist datasets on the data portal and view the complete data model of the lobbyist database here: https://services.austintexas.gov/edims/document.cfm?id=293053

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

A look up table of each due date associated with a lobbyist's quarterly activity report. You can recreate the City Clerk's lobbyist database by downloading all lobbyist datasets on the data portal and view the complete data model of the lobbyist database here: https://services.austintexas.gov/edims/document.cfm?id=293053

This Address Standards document has been developed to describe the addressing standards used for the Master Address Repository (MAR). The MAR is DC Government’s official address database and is widely used across the City of Washington, DC. The OCTO Data Team which is part of the Office of the Chief Technology Officer (OCTO), is responsible for maintaining the MAR.

There is no abstract created for this record There is no abstract created for this record

This dataset lists each employee a lobbyist reports. You can recreate the City Clerk's lobbyist database by downloading all lobbyist datasets on the data portal and view the complete data model of the lobbyist database here: https://services.austintexas.gov/edims/document.cfm?id=293053

This table lists each real property associated with a lobbyist's municipal question. You can recreate the City Clerk's lobbyist database by downloading all lobbyist datasets on the data portal and view the complete data model of the lobbyist database here: https://www.austintexas.gov/edims/document.cfm?id=293053

This dataset lists each expenditure reported by a lobbyist. You can recreate the City Clerk's lobbyist database by downloading all lobbyist datasets on the data portal and view the complete data model of the lobbyist database here: https://services.austintexas.gov/edims/document.cfm?id=293053

This dataset contains aggregated data for fiscal years 2006-2020 from the Institute of Museum and Library Services' annual public library survey. This transformed version of the data contains aggregated data by material type for all public libraries in the nation, as well as an additional subset of the data for aggregated data by material type for Oklahoma's public libraries. Column headers include: Year, Print Materials, Electronic Materials, Other Materials, and Total. Material categories represent: material expenditures for physical materials (books, current serial subscriptions, government documents, and any other print acquisitions), electronic materials (ebooks, e-serials, government documents, databases, electronic files, reference tools, scores, maps, or pictures, including materials digitized by the library), and other materials (microform, audio, video, DVD, and new formats). These values were directly pulled from corresponding datasets for each public library from the PRMATEXP, ELMATEXP, and OTHMATEX columns, representing physical, electronic, and other material expenditures, respectively. Negative and zero values (-3, -1, 0) were excluded from categorical tallies, with -3 values representing closed or temporarily closed administrative entities. No explanation for -1 or 0 values was present in IMLS documentation. Valued were tallied by column after negative and zero values were excluded, with final tallies for each data column included in the attached dataset. Lastly, annually tallied were summed by each year in both National and State datasets. Two sets of the data are available: One set with two tabs (one each for National and State spending) in an Excel format, and two separate files (one each for National and State spending) in a CSV format.

A relational hydrogeologic database (HYDAT) has been developed using Paradox for Windows. HYDAT realistically models water well and hydrogeologic data using a simplified set of attributes considered to be those of primary importance to the... A relational hydrogeologic database (HYDAT) has been developed using Paradox for Windows. HYDAT realistically models water well and hydrogeologic data using a simplified set of attributes considered to be those of primary importance to the hydrogeologist. Data integrity relationships are forced during data entry, additionally data integrity/regeneration scanning procedures are provided. Queries, which may involve the generation of real and imaginary (possible time dependant) surfaces for wells, which may themselves satisfy complex selection criteria, are discussed.

The table also reveals the number of scientific papers cited by these institutions and the number of climate change papers (the number in brackets is the number of policy documents citing the climate change papers).

Iowa Public Employment Relations Board (PERB) electronic research and retrieval database system. This system provides access to full-text documents including: Contracts, Contracts Archive, PERB and Court Decisions, and Neutral Decisions.

Contracts – Contracts published and included in this database are only those forwarded to PERB by the parties. Contracts Archive – Contracts that were forwarded to PERB and have expired, beginning with those that expired in 2008, are included in this database.

PERB and Court Decisions – In this database, the PERB decisions do not include routine or preliminary rulings and orders issued by PERB, but include only substantive final agency decisions and non-final rulings and orders deemed informative. Court decisions are those on judicial review of PERB decisions.

Neutral Decisions – The neutral decisions database includes recent and a number of prior years’ fact-finding and interest arbitration decisions. Additionally, it includes only those grievance arbitration decisions forwarded to PERB for publication by the arbitrator with consent of the parties involved. Click on the Contents tab of the database to view all documents contained in the database.

PERB decisions do not include routine or preliminary rulings and orders issued by PERB, but include only substantive final agency decisions and non-final rulings and orders deemed informative. Court decisions are those on judicial review of PERB decisions.

Serverless NoSQL Database Market Outlook

According to our latest research, the Global Serverless NoSQL Database market size was valued at $2.8 billion in 2024 and is projected to reach $13.6 billion by 2033, expanding at a robust CAGR of 19.2% during the forecast period of 2025–2033. The primary driver fueling this remarkable growth is the surging demand for highly scalable, low-latency data management solutions that can seamlessly support modern, cloud-native applications across diverse industries. As organizations increasingly migrate to digital-first strategies, the need for flexible, cost-efficient, and maintenance-free database architectures is accelerating the adoption of serverless NoSQL databases worldwide. This transformation is further amplified by the proliferation of real-time analytics, IoT deployments, and mobile-first services, all of which require agile data storage and retrieval capabilities that traditional database models struggle to deliver.

Regional Outlook

North America currently dominates the serverless NoSQL database market, commanding the largest share with over 38% of global revenues in 2024. This leadership is largely attributed to the region’s mature cloud ecosystem, early adoption of serverless technologies, and the presence of tech giants such as Amazon Web Services, Google, and Microsoft, who are continuously innovating within this space. Favorable regulatory frameworks, a robust startup culture, and significant investments in digital transformation initiatives across industries like BFSI, healthcare, and retail further bolster the region’s dominance. Moreover, North American enterprises are at the forefront of leveraging advanced analytics, artificial intelligence, and IoT, all of which necessitate the high availability and scalability offered by serverless NoSQL databases.

Asia Pacific is emerging as the fastest-growing region in the serverless NoSQL database market, projected to expand at a remarkable CAGR of 23.5% through 2033. Rapid digitization, government-led smart city initiatives, and the exponential growth of mobile and IoT applications are key factors propelling market expansion in countries such as China, India, Japan, and South Korea. Additionally, the increasing penetration of cloud computing and the rising number of tech-savvy SMEs are driving demand for flexible, cost-effective database solutions. Major cloud service providers are also ramping up their investments and partnerships in the region, making advanced database technologies more accessible to a broader spectrum of enterprises.

In contrast, emerging economies in Latin America, the Middle East, and Africa are experiencing a gradual but steady uptake of serverless NoSQL database solutions. While these regions face challenges such as limited cloud infrastructure, skills shortages, and regulatory uncertainties, localized demand for digital services, especially in e-commerce, fintech, and media, is driving adoption. Governments are beginning to recognize the economic potential of digital transformation and are implementing supportive policies and incentives. However, organizations in these regions must navigate issues related to data sovereignty, connectivity, and vendor lock-in, which may moderate the pace of market penetration compared to more developed regions.

Report Scope

[Note: Integrated as part of FoodData Central, April 2019.] The database consists of several sets of data: food descriptions, nutrients, weights and measures, footnotes, and sources of data. The Nutrient Data file contains mean nutrient values per 100 g of the edible portion of food, along with fields to further describe the mean value. Information is provided on household measures for food items. Weights are given for edible material without refuse. Footnotes are provided for a few items where information about food description, weights and measures, or nutrient values could not be accommodated in existing fields. Data have been compiled from published and unpublished sources. Published data sources include the scientific literature. Unpublished data include those obtained from the food industry, other government agencies, and research conducted under contracts initiated by USDA’s Agricultural Research Service (ARS). Updated data have been published electronically on the USDA Nutrient Data Laboratory (NDL) web site since 1992. Standard Reference (SR) 28 includes composition data for all the food groups and nutrients published in the 21 volumes of "Agriculture Handbook 8" (US Department of Agriculture 1976-92), and its four supplements (US Department of Agriculture 1990-93), which superseded the 1963 edition (Watt and Merrill, 1963). SR28 supersedes all previous releases, including the printed versions, in the event of any differences. Attribution for photos: Photo 1: k7246-9 Copyright free, public domain photo by Scott Bauer Photo 2: k8234-2 Copyright free, public domain photo by Scott Bauer Resources in this dataset:Resource Title: READ ME - Documentation and User Guide - Composition of Foods Raw, Processed, Prepared - USDA National Nutrient Database for Standard Reference, Release 28. File Name: sr28_doc.pdfResource Software Recommended: Adobe Acrobat Reader,url: http://www.adobe.com/prodindex/acrobat/readstep.html Resource Title: ASCII (6.0Mb; ISO/IEC 8859-1). File Name: sr28asc.zipResource Description: Delimited file suitable for importing into many programs. The tables are organized in a relational format, and can be used with a relational database management system (RDBMS), which will allow you to form your own queries and generate custom reports.Resource Title: ACCESS (25.2Mb). File Name: sr28db.zipResource Description: This file contains the SR28 data imported into a Microsoft Access (2007 or later) database. It includes relationships between files and a few sample queries and reports.Resource Title: ASCII (Abbreviated; 1.1Mb; ISO/IEC 8859-1). File Name: sr28abbr.zipResource Description: Delimited file suitable for importing into many programs. This file contains data for all food items in SR28, but not all nutrient values--starch, fluoride, betaine, vitamin D2 and D3, added vitamin E, added vitamin B12, alcohol, caffeine, theobromine, phytosterols, individual amino acids, individual fatty acids, or individual sugars are not included. These data are presented per 100 grams, edible portion. Up to two household measures are also provided, allowing the user to calculate the values per household measure, if desired.Resource Title: Excel (Abbreviated; 2.9Mb). File Name: sr28abxl.zipResource Description: For use with Microsoft Excel (2007 or later), but can also be used by many other spreadsheet programs. This file contains data for all food items in SR28, but not all nutrient values--starch, fluoride, betaine, vitamin D2 and D3, added vitamin E, added vitamin B12, alcohol, caffeine, theobromine, phytosterols, individual amino acids, individual fatty acids, or individual sugars are not included. These data are presented per 100 grams, edible portion. Up to two household measures are also provided, allowing the user to calculate the values per household measure, if desired.Resource Software Recommended: Microsoft Excel,url: https://www.microsoft.com/ Resource Title: ASCII (Update Files; 1.1Mb; ISO/IEC 8859-1). File Name: sr28upd.zipResource Description: Update Files - Contains updates for those users who have loaded Release 27 into their own programs and wish to do their own updates. These files contain the updates between SR27 and SR28. Delimited file suitable for import into many programs.