Autonomous Data Platform Market Size & Share Analysis - Growth Trends & Forecasts (2025 - 2030)

The Autonomous Data Platform Market is Segmented by Organization Size (Large Enterprises, and Small and Medium-Sized Enterprises (SMEs)), Deployment Type (Public Cloud, Private Cloud and More), End-User Vertical (BFSI. Healthcare and Life Sciences and More), Component (Platform / Solution and Services), Data Type (Structured Data and Semi-Structured Data), and Geography. The Market Forecasts are Provided in Terms of Value (USD).

Autonomous Data Platform Market Size and Share

Autonomous Data Platform Market (2025 - 2030)
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Autonomous Data Platform Market Analysis by Mordor Intelligence

The autonomous data platform market reached USD 2.13 billion in 2025 and is forecast to climb to USD 5.37 billion by 2030, expanding at a 20.33% CAGR. This growth path shows how enterprises are shifting from manually tuned data stacks toward fully autonomous, AI-first operations that reduce human intervention in storage, optimization, and lifecycle management. Cloud hyperscalers have turned autonomy into a core feature of their infrastructure portfolios, allowing users to provision, govern, and scale databases without specialized skills. Falling storage costs now let companies keep petabyte-scale historical data online, improving model accuracy and time-series analytics at manageable budgets. At the same time, regional data-sovereignty laws force organizations to architect multiregional replication strategies, creating demand for platforms that deliver low-latency performance while still enforcing residency controls. Competitive intensity is rising as established database vendors, lake house specialists, and hyperscalers race to embed automated performance tuning, self-healing features, and integrated Gen-AI copilots that democratize complex tasks.

Key Report Takeaways

  • By organization size, large enterprises held 62% of the autonomous data platform market share in 2024, while small and medium-sized enterprises are advancing at a 26% CAGR through 2030.  
  • By deployment type, the public-cloud segment captured 54% revenue share in 2024; hybrid configurations are forecast to expand at a 29% CAGR to 2030.  
  • By end-user vertical, banking, financial services, and insurance led with a 28% share of the autonomous data platform market size in 2024, whereas healthcare and life sciences are growing at a 25% CAGR through 2030.  
  • By component, platform and solution offerings accounted for a 70% share in 2024, while managed services are expanding at a 27% CAGR to 2030.  
  • By data type, unstructured data processing commanded a 57% share of the autonomous data platform market size in 2024, and semi-structured workloads are rising at a 31% CAGR through 2030.  
  • By geography, North America led with 41% revenue share in 2024; the Asia-Pacific region is on track for a 23% CAGR to 2030.

Segment Analysis

By Organization Size: SMEs Advance Platform Democratization

Large enterprises currently generate most revenue with a market share of 62%, yet small and medium-sized firms fuel the fastest expansion of the autonomous data platform market. The autonomous data platform market size attributable to SMEs is projected to widen swiftly thanks to natural-language copilots that replace code-heavy interfaces. Prophecy’s transformation assistant lets functional teams at consumer-focused brands orchestrate data flows without engineering backlogs. Meanwhile, mega-enterprises rely on federated data-mesh rollouts across geographies and business units, driving complex governance implementations that sustain platform vendors’ enterprise licensing streams.

SMEs view autonomous data tools as an equalizer that shortens innovation cycles. Case studies such as F45 Training’s deployment with Fiveonefour illustrate tangible returns, reporting 50% cost reductions and 10× faster development cycles on consumer analytics pipelines. As accessible pricing tiers spread, the autonomous data platform market gains a broader long-tail customer base, challenging vendors to maintain usability while preserving advanced enterprise functionality.

Autonomous Data Platform Market: Market Share by Organization Size
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By Deployment Type: Hybrid Configurations Address Sovereignty Requirements

Public-cloud services deliver the bulk of current spending, yet hybrid models expand at a pace that reshapes the autonomous data platform market. Sovereignty concerns and performance optimization drive enterprises to keep sensitive workloads on-premises while bursting analytics and AI training to scalable public resources. Deutsche Bank’s phased data-platform migration blended on-premises systems with Google Cloud services for 20 million customers, proving hybrid’s compliance value.  

The autonomous data platform market size tied to hybrid deployments is forecast to accelerate as frameworks such as the EU Data Act compel portability. Oracle’s Cloud@Customer nodal offering appeals to firms seeking public-cloud autonomy inside private facilities, indicating that location-agnostic control planes will define competitive positioning. Pure private-cloud growth slows because in-house hardware and skills cannot match public-cloud innovation velocity, nudging firms toward hybrid compromises.

By End-User Vertical: Healthcare Accelerates Through AI Integration

BFSI remains the single largest adopter with 28%, yet healthcare and life sciences produce the steepest trajectories in the autonomous data platform market. Banking institutions employ real-time risk scoring to meet tightening capital and liquidity mandates, whereas pharmaceutical leaders such as Sanofi use autonomous lake houses to speed analysis of real-world clinical data.  

Health-sector growth is amplified by vast image, genomic, and clinical-trial files that benefit from autonomous scaling and policy-based lifecycle management. Sanofi reported accelerated drug-discovery analytics after moving workloads to Snowpark, underscoring the sector’s appetite for turnkey compliance and compute elasticity. Consequently, vendors craft HIPAA-ready blueprints and 21 CFR Part 11 attestations to win share as the autonomous data platform market expands in regulated life-science domains.

Autonomous Data Platform Market: Market Share by End-user Vertical
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Note: Segment shares of all individual segments available upon report purchase

By Component: Managed Services Address Complexity Challenges

Platform software still captures most spending, yet managed services record the sharpest climbs because many enterprises outsource operations that exceed internal abilities. Fidelity Investments operates hundreds of models but cautions that creativity must coexist with governance, inspiring demand for managed MLOps orchestration. The autonomous data platform market size credited to managed services will keep widening as organizations favour outcome-based contracts that guarantee uptime, latency, and cost thresholds.  

Vendors respond by bundling run-operations with product licenses or partnering with service specialists. ServiceNow’s acquisition of data. World shows how cataloging, lineage, and workflow automation converge under service umbrellas, offering a cradle-to-grave data pipeline managed by one provider. Differentiation increasingly hinges on measurable value such as performance benchmarks and financial savings rather than feature lists alone.

Geography Analysis

North America commanded 41% of autonomous data platform market share in 2024, underpinned by early adoption of AI-first strategies and substantial data-center investments. Amazon alone plans USD 150 billion for additional facilities that will run GPU clusters needed for large language models. Oracle’s infrastructure revenue surged 70% year-over-year in fiscal 2025 as enterprises embraced self-tuning databases that meet stringent uptime and compliance standards. A mature venture ecosystem funds specialized startups focusing on data observability, cataloging, and real-time AI, further enriching the regional technology stack.

The Asia-Pacific region shows the fastest CAGR at 23%, driven by India’s data-protection framework and Japan’s AI Basic Law proposal, both of which require tightly governed yet innovation-friendly platforms. Government programs funding digital public infrastructure shorten procurement cycles, letting firms adopt autonomous solutions early in their modernization journeys. Hyperscalers rapidly expand local zones to meet residency rules, while regional service providers create sovereign platforms that integrate with global clouds through standardized APIs.

Europe sustains growth through privacy leadership and the new Data Act, which mandates vendor-agnostic portability. Platform providers respond with open-format catalogs and zero-copy data-sharing innovations to reduce exit friction. The region’s insistence on explainability and audit trails favors autonomous platforms that embed lineage tracking and AI model governance by default. South America, the Middle East, and Africa trail in current adoption but show high project pipelines as telecom operators, banks, and public agencies pursue cloud-first roadmaps that leapfrog legacy infrastructure. [3]Matt Day, “Amazon Bets $150 Billion on Data Centers Required for AI Boom,” Bloomberg, bloomberg.com

Autonomous Data Platform Market CAGR (%), Growth Rate by Region
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Competitive Landscape

Competition centers on a handful of scale players contending with nimble specialists. Snowflake, Databricks, Oracle, and the hyperscale clouds invest heavily in autonomous optimizers, Gen-AI assistants, and cross-cloud interoperability. Snowflake’s patent portfolio spans adaptive query aggregation and zero-copy sharing, reinforcing its data-cloud vision. Databricks fuses structured and unstructured analytics under the lakehouse, while Oracle touts self-patching databases that run on dedicated, security-hardened hardware.

Acquisition activity underscores the premium on differentiated AI capabilities. Snowflake’s planned purchase of Crunchy Data aims to bring fully managed PostgreSQL into its ecosystem, whereas IBM’s intent to buy DataStax targets NoSQL and vector search features vital for retrieval-augmented generation. ServiceNow’s move for data. world blends workflow orchestration with cataloging, extending platform influence deeper into operational processes.

Emerging ventures focus on data mesh, domain accelerators, and observability. Many position themselves as neutral layers that sit above hyperscalers, promising reduced lock-in. Patent filings on auto-indexing, cache management, and privacy-preserving query rewrite signal perpetual innovation. Price competition intensifies around storage compression and autonomous workload placement, while value discussions shift toward measurable outcomes such as time-to-insight and cost-per-query rather than raw capacity. [4]Chris Zeoli, “Data platforms Snowflake and Databricks acquiring model developers,” DataGravity, datagravity.dev

Autonomous Data Platform Industry Leaders

  1. Amazon Web Services, Inc.

  2. Microsoft Corporation

  3. Snowflake Inc.

  4. Oracle Corporation

  5. Databricks, Inc.

  6. *Disclaimer: Major Players sorted in no particular order
Oracle Corporation, International Business Machines Corporation, Amazon Web Services, Teradata Corporation, Qubole Inc
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Recent Industry Developments

  • June 2025: Snowflake announced agreement to acquire Crunchy Data to create an enterprise-ready PostgreSQL service.
  • June 2025: Oracle reported fiscal 2025 Q4 revenue of USD 15.9 billion with cloud revenue at USD 6.7 billion, predicting >40% cloud growth in fiscal 2026.
  • June 2025: Databricks projected annualized revenue of USD 3.7 billion with nearly 50 clients each spending over USD 10 million.
  • May 2025: ServiceNow acquired data.world to augment cataloging and governance capabilities.

Table of Contents for Autonomous Data Platform Industry Report

1. INTRODUCTION

  • 1.1 Study Assumptions and Market Definition
  • 1.2 Scope of the Study

2. RESEARCH METHODOLOGY

3. EXECUTIVE SUMMARY

4. MARKET LANDSCAPE

  • 4.1 Market Overview
  • 4.2 Market Drivers
    • 4.2.1 AI-first data-ops strategies adopted by cloud hyperscalers
    • 4.2.2 Rapid fall in data-storage cost enabling petabyte-scale ingestion
    • 4.2.3 Rising enterprise move toward data-mesh and fabric architectures
    • 4.2.4 Mandatory data-residency/sovereign-cloud rules in Europe and APAC
    • 4.2.5 Integration of Gen-AI copilots for low-code data engineering
    • 4.2.6 Industry-specific packaged analytics accelerators (banking, life-science)
  • 4.3 Market Restraints
    • 4.3.1 Ongoing skills gap for composite AI and MLOps orchestration
    • 4.3.2 Escalating cloud egress fees impacting TCO
    • 4.3.3 Persistent security debt from legacy ETL pipelines
    • 4.3.4 Vendor lock-in concerns hindering multicloud portability
  • 4.4 Value / Supply-Chain Analysis
  • 4.5 Regulatory Landscape
  • 4.6 Technological Outlook
  • 4.7 Porter's Five Forces Analysis
    • 4.7.1 Threat of New Entrants
    • 4.7.2 Bargaining Power of Buyers
    • 4.7.3 Bargaining Power of Suppliers
    • 4.7.4 Threat of Substitutes
    • 4.7.5 Intensity of Competitive Rivalry

5. MARKET SIZE AND GROWTH FORECASTS (VALUE)

  • 5.1 By Organization Size
    • 5.1.1 Large Enterprises
    • 5.1.2 Small and Medium-Sized Enterprises (SMEs)
  • 5.2 By Deployment Type
    • 5.2.1 Public Cloud
    • 5.2.2 Private Cloud
    • 5.2.3 Hybrid Cloud
  • 5.3 By End-user Vertical
    • 5.3.1 Banking, Financial Services and Insurance (BFSI)
    • 5.3.2 Healthcare and Life Sciences
    • 5.3.3 Retail and Consumer Goods
    • 5.3.4 Media and Telecommunications
    • 5.3.5 Government and Public Sector
    • 5.3.6 Manufacturing
  • 5.4 By Component
    • 5.4.1 Platform / Solution
    • 5.4.2 Services
    • 5.4.2.1 Professional Services
    • 5.4.2.2 Managed Services
  • 5.5 By Data Type
    • 5.5.1 Structured Data
    • 5.5.2 Semi-Structured Data
    • 5.5.3 Unstructured Data
  • 5.6 By Geography
    • 5.6.1 North America
    • 5.6.1.1 United States
    • 5.6.1.2 Canada
    • 5.6.1.3 Mexico
    • 5.6.2 South America
    • 5.6.2.1 Brazil
    • 5.6.2.2 Argentina
    • 5.6.2.3 Rest of South America
    • 5.6.3 Europe
    • 5.6.3.1 United Kingdom
    • 5.6.3.2 Germany
    • 5.6.3.3 France
    • 5.6.3.4 Italy
    • 5.6.3.5 Spain
    • 5.6.3.6 Russia
    • 5.6.3.7 Rest of Europe
    • 5.6.4 Asia-Pacific
    • 5.6.4.1 China
    • 5.6.4.2 Japan
    • 5.6.4.3 India
    • 5.6.4.4 South Korea
    • 5.6.4.5 Australia and New Zealand
    • 5.6.4.6 Rest of Asia-Pacific
    • 5.6.5 Middle East and Africa
    • 5.6.5.1 Middle East
    • 5.6.5.1.1 Saudi Arabia
    • 5.6.5.1.2 United Arab Emirates
    • 5.6.5.1.3 Turkey
    • 5.6.5.1.4 Rest of Middle East
    • 5.6.5.2 Africa
    • 5.6.5.2.1 South Africa
    • 5.6.5.2.2 Rest of Africa

6. COMPETITIVE LANDSCAPE

  • 6.1 Market Concentration
  • 6.2 Strategic Moves
  • 6.3 Market Share Analysis
  • 6.4 Company Profiles (includes Global level Overview, Market level overview, Core Segments, Financials as available, Strategic Information, Market Rank/Share for key companies, Products and Services, and Recent Developments)
    • 6.4.1 Oracle Corporation
    • 6.4.2 International Business Machines Corporation
    • 6.4.3 Amazon Web Services, Inc.
    • 6.4.4 Teradata Corporation
    • 6.4.5 Qubole, Inc.
    • 6.4.6 MapR Technologies, Inc.
    • 6.4.7 Snowflake Inc.
    • 6.4.8 Microsoft Corporation
    • 6.4.9 Google LLC
    • 6.4.10 Cloudera, Inc.
    • 6.4.11 Databricks, Inc.
    • 6.4.12 Alteryx, Inc.
    • 6.4.13 Ataccama Corporation
    • 6.4.14 Gemini Data, Inc.
    • 6.4.15 Denodo Technologies, Inc.
    • 6.4.16 Zaloni, Inc.
    • 6.4.17 Informatica Inc.
    • 6.4.18 Paxata, Inc.
    • 6.4.19 Dremio Corporation
    • 6.4.20 Talend Inc.

7. MARKET OPPORTUNITIES AND FUTURE OUTLOOK

  • 7.1 White-space and Unmet-Need Assessment
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Global Autonomous Data Platform Market Report Scope

An autonomous data tool analyzes a specific customer's big data infrastructure to address essential business problems and assure optimal database usage. This supports businesses to develop and enhance their data management abilities. They are specifically created to control and optimize big data infrastructure. Many firms are embracing this platform because it encourages the IT professional to manage processes more efficiently.

By Organization Size Large Enterprises
Small and Medium-Sized Enterprises (SMEs)
By Deployment Type Public Cloud
Private Cloud
Hybrid Cloud
By End-user Vertical Banking, Financial Services and Insurance (BFSI)
Healthcare and Life Sciences
Retail and Consumer Goods
Media and Telecommunications
Government and Public Sector
Manufacturing
By Component Platform / Solution
Services Professional Services
Managed Services
By Data Type Structured Data
Semi-Structured Data
Unstructured Data
By Geography North America United States
Canada
Mexico
South America Brazil
Argentina
Rest of South America
Europe United Kingdom
Germany
France
Italy
Spain
Russia
Rest of Europe
Asia-Pacific China
Japan
India
South Korea
Australia and New Zealand
Rest of Asia-Pacific
Middle East and Africa Middle East Saudi Arabia
United Arab Emirates
Turkey
Rest of Middle East
Africa South Africa
Rest of Africa
By Organization Size
Large Enterprises
Small and Medium-Sized Enterprises (SMEs)
By Deployment Type
Public Cloud
Private Cloud
Hybrid Cloud
By End-user Vertical
Banking, Financial Services and Insurance (BFSI)
Healthcare and Life Sciences
Retail and Consumer Goods
Media and Telecommunications
Government and Public Sector
Manufacturing
By Component
Platform / Solution
Services Professional Services
Managed Services
By Data Type
Structured Data
Semi-Structured Data
Unstructured Data
By Geography
North America United States
Canada
Mexico
South America Brazil
Argentina
Rest of South America
Europe United Kingdom
Germany
France
Italy
Spain
Russia
Rest of Europe
Asia-Pacific China
Japan
India
South Korea
Australia and New Zealand
Rest of Asia-Pacific
Middle East and Africa Middle East Saudi Arabia
United Arab Emirates
Turkey
Rest of Middle East
Africa South Africa
Rest of Africa
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Key Questions Answered in the Report

.What is the current size and growth outlook for the autonomous data platform market?

The autonomous data platform market reached USD 2.13 billion in 2025 and is on course for USD 5.37 billion by 2030, posting a 20.33% CAGR.

Which deployment model is growing fastest?

Hybrid cloud configurations are expanding at a 29% CAGR as firms balance latency, cost, and data-sovereignty obligations.

Why are healthcare and life-science firms adopting autonomous data platforms rapidly?

They need to process large clinical and genomic datasets securely and at speed, driving a 25% CAGR for the vertical through 2030.

How do sovereignty regulations influence platform choice?

Mandates such as the EU Data Act require easy portability and local data residency, pushing enterprises toward providers with multiregional compliance features.

What role do managed services play in adoption?

Managed services offset skills shortages in MLOps and governance, growing at a 27% CAGR as organizations seek turnkey operations.

What is the biggest technical restraint hindering wider rollout?

A persistent skills gap in composite AI and distributed MLOps orchestration slows enterprise ability to harness full autonomy, reducing overall CAGR by an estimated 2.8%.

Page last updated on: July 10, 2025

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