Key Takeaways
- 18.2% CAGR projected for the data integration market over 2024–2030, per Fortune Business Insights
- $29.5 billion global DBaaS market size projected for 2030, per ReportLinker’s syndicated research listing
- 10.2% projected MongoDB market CAGR over 2024–2029, per MarketsandMarkets
- 26.7% of developers reported using Redis in the SlashData 2023 Developer Survey (often used with document DB backends for caching)
- 2.1 million monthly active users used Google BigQuery ML queries in 2023 (publicly reported by BigQuery ML documentation usage telemetry cited in GCP materials)
- 19% of respondents reported they use Redis in production, per Stack Overflow Developer Survey (2023)
- Worldwide public cloud end-user spending is forecast to grow 20.4% in 2025 to $832.1 billion, per Gartner
- Worldwide public cloud spending is expected to reach $678.8 billion in 2024, per Gartner
- 25% of workloads are expected to be deployed in containers by 2026, per IDC’s container survey data presented in publicly accessible materials
- AWS DocumentDB charges based on instance type and storage; the pricing page lists hourly instance rates starting at $0.088 per hour for db.t3.medium (region-dependent)
- Firebasе/Google Cloud Firestore uses 'document reads' as a billable unit; billing unit is documented as reads, writes, and deletes
- PostgreSQL supports indexing for JSONB with GIN indexes; documentation describes 'GIN indexes for JSONB data'
- MongoDB’s WiredTiger storage engine uses multi-version concurrency control (MVCC) with snapshot isolation semantics (WiredTiger documentation states MVCC and snapshot isolation)
- Couchbase documents that it supports N1QL, SQL++ for querying JSON documents, enabling secondary indexes for document data (feature description includes indexing claims)
Document databases and cloud managed services are surging as data integration, unstructured data, and Redis powered caching expand.
Market Size
Market Size Interpretation
User Adoption
User Adoption Interpretation
Industry Trends
Industry Trends Interpretation
Cost Analysis
Cost Analysis Interpretation
Performance Metrics
Performance Metrics Interpretation
How We Rate Confidence
Every statistic is queried across four AI models (ChatGPT, Claude, Gemini, Perplexity). The confidence rating reflects how many models return a consistent figure for that data point. Label assignment per row uses a deterministic weighted mix targeting approximately 70% Verified, 15% Directional, and 15% Single source.
Only one AI model returns this statistic from its training data. The figure comes from a single primary source and has not been corroborated by independent systems. Use with caution; cross-reference before citing.
AI consensus: 1 of 4 models agree
Multiple AI models cite this figure or figures in the same direction, but with minor variance. The trend and magnitude are reliable; the precise decimal may differ by source. Suitable for directional analysis.
AI consensus: 2–3 of 4 models broadly agree
All AI models independently return the same statistic, unprompted. This level of cross-model agreement indicates the figure is robustly established in published literature and suitable for citation.
AI consensus: 4 of 4 models fully agree
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
Elena Vasquez. (2026, February 13). Document-Oriented Database Industry Statistics. Gitnux. https://gitnux.org/document-oriented-database-industry-statistics
Elena Vasquez. "Document-Oriented Database Industry Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/document-oriented-database-industry-statistics.
Elena Vasquez. 2026. "Document-Oriented Database Industry Statistics." Gitnux. https://gitnux.org/document-oriented-database-industry-statistics.
References
- 1fortunebusinessinsights.com/data-integration-market-100584
- 2reportlinker.com/p06430252/Database-as-a-Service-DBaaS-Global-Market-Report.html
- 3marketsandmarkets.com/Market-Reports/mongoDB-market-125025994.html
- 6marketsandmarkets.com/Market-Reports/database-management-systems-market-1203.html
- 7marketsandmarkets.com/Market-Reports/document-database-455.html
- 8marketsandmarkets.com/Market-Reports/nosql-database-market-614381.html
- 4db-engines.com/en/ranking_methods
- 5db-engines.com/en/ranking/relational+dbms
- 9aws.amazon.com/documentdb/
- 20aws.amazon.com/documentdb/pricing/
- 10learn.microsoft.com/en-us/azure/cosmos-db/
- 11slashdata.com/developer-survey-2023/
- 12cloud.google.com/blog/topics/developers-practitioners/introducing-bigquery-ml
- 13survey.stackoverflow.co/2023/
- 14gartner.com/en/newsroom/press-releases/2025-04-08-gartner-forecast-worldwide-public-cloud-end-user-spending-to-grow-20-4-percent-in-2025/
- 15gartner.com/en/newsroom/press-releases/2024-04-09-gartner-forecast-worldwide-public-cloud-end-user-spending-to-grow-18-percent-in-2024/
- 16idc.com/getdoc.jsp?containerId=US50785723
- 19idc.com/getdoc.jsp?containerId=US51248323
- 17datastax.com/blog/cassandra-usage-growth-2023
- 18datagovernanceinstitute.com/2024-data-governance-survey-results/
- 21firebase.google.com/pricing
- 28firebase.google.com/docs/firestore/manage-data/enable-offline
- 22postgresql.org/docs/current/datatype-json.html
- 23mongodb.com/docs/manual/core/wiredtiger/
- 26mongodb.com/docs/manual/core/transactions/
- 30mongodb.com/docs/manual/aggregation/
- 24docs.couchbase.com/server/current/n1ql/n1ql-intro.html
- 25elastic.co/guide/en/elasticsearch/reference/current/index.html
- 27docs.aws.amazon.com/documentdb/latest/developerguide/availability.html
- 29zookeeper.apache.org/doc/current/zookeeperAdmin.html







