MLOps is the process of taking an experimental Machine Learning model into a production system. The word is a compound of 鈥淢achine Learning鈥� and the continuous development practice of DevOps in the software field. Machine Learning models are tested and developed in isolated experimental systems. When an algorithm is ready to be launched, MLOps is practiced between Data Scientists, DevOps, and Machine Learning engineers to transition the algorithm to production systems. Similar to DevOps or DataOps approaches, MLOps seeks to increase automation and improve the quality of production models, while also focusing on business and regulatory requirements. While MLOps started as a set of best practices, it is slowly evolving into an independent approach to ML lifecycle management. MLOps applies to the entire lifecycle - from integrating with model generation (software development lifecycle, continuous integration/continuous delivery), orchestration, and deployment, to health, diagnostics, governance, and business metrics.
The global market for Machine Learning Operations (MLOps) was estimated to be worth US$ 545.5 million in 2023 and is forecast to a readjusted size of US$ 9066.7 million by 2030 with a CAGR of 41.8% during the forecast period 2024-2030.
The key vendors providing Machine Learning Operations (MLOps) worldwide are IBM, DataRobot, SAS, Microsoft, Amazon, Google, Dataiku, Databricks, and others. The top five vendors together hold over 45% of the market share, with the largest producer being IBM with 10% of the market share. The major regions offering machine learning operations globally are North America, Europe, China, and the Middle East. In terms of their product categories, on-premise type have the highest market share at over 55%, followed by cloud MLOps at 35%. In terms of its applications, BFSI is its top application area, with over 25% market share, followed by the public sector and manufacturing.
Report Scope
This report aims to provide a comprehensive presentation of the global market for Machine Learning Operations (MLOps), with both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyse their position in the current marketplace, and make informed business decisions regarding Machine Learning Operations (MLOps).
The Machine Learning Operations (MLOps) market size, estimations, and forecasts are provided in terms of and revenue ($ millions), considering 2023 as the base year, with history and forecast data for the period from 2019 to 2030. This report segments the global Machine Learning Operations (MLOps) market comprehensively. Regional market sizes, concerning products by type, by application, and by players, are also provided.
For a more in-depth understanding of the market, the report provides profiles of the competitive landscape, key competitors, and their respective market ranks. The report also discusses technological trends and new product developments.
The report will help the Machine Learning Operations (MLOps) companies, new entrants, and industry chain related companies in this market with information on the revenues for the overall market and the sub-segments across the different segments, by company, product type, application, and regions.
Market Segmentation
By Company
IBM
DataRobot
SAS
Microsoft
Amazon
Google
Dataiku
Databricks
HPE
Lguazio
ClearML
Modzy
Comet
Cloudera
Paperpace
Valohai
Segment by Type
On-premise
Cloud
Others
Segment by Application
BFSI
Healthcare
Retail
Manufacturing
Public Sector
Others
By Region
North America
United States
Canada
Europe
Germany
France
U.K.
Italy
Russia
Nordic Countries
Rest of Europe
Asia-Pacific
China
Japan
South Korea
India
Southeast Asia
Australia
Rest of Asia-Pacific
Latin America
Mexico
Brazil
Rest of Latin America
Middle East & Africa
Turkey
Saudi Arabia
UAE
Rest of Middle East & Africa
Chapter Outline
Chapter 1: Introduces the report scope of the report, executive summary of different market segments (product type, application, etc), including the market size of each market segment, future development potential, and so on.
Chapter 2: Revenue of Machine Learning Operations (MLOps) in global and regional level.
Chapter 3: Detailed analysis of Machine Learning Operations (MLOps) company competitive landscape, revenue, market share and industry ranking, latest development plan, merger, and acquisition information, etc.
Chapter 4: Provides profiles of key companies, introducing the basic situation of the main companies in the market in detail, including product descriptions and specifications, Machine Learning Operations (MLOps) revenue, gross margin, and recent development, etc.
Chapter 5: Provides the analysis of various market segments by Type, covering the revenue, and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 6: Provides the analysis of various market segments by Application, covering the revenue, and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 7: North America (US & Canada) by Type, by Application and by country, revenue for each segment.
Chapter 8: Europe by Type, by Application and by country, revenue for each segment.
Chapter 9: Asia Pacific by Type, by Application and by region, revenue for each segment.
Chapter 10: Latin America by Type, by Application and by country, revenue for each segment.
Chapter 11: Middle East and Africa, by Type, by Application and by country, revenue for each segment.
Chapter 12: Analysis of industrial chain, sales channel, key raw materials, distributors, and customers.
Chapter 13: Introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by manufacturers in the industry, and the analysis of relevant policies in the industry.
Chapter 14: Research Findings and Conclusion
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1 Study Coverage
1.1 Machine Learning Operations (MLOps) Product Introduction
1.2 Market by Type
1.2.1 Global Machine Learning Operations (MLOps) Market Size Growth Rate by Type (2019 VS 2023 VS 2030)
1.2.2 On-premise
1.2.3 Cloud
1.2.4 Others
1.3 Market by Application
1.3.1 Global Machine Learning Operations (MLOps) Market Size Growth Rate by Application (2019 VS 2023 VS 2030)
1.3.2 BFSI
1.3.3 Healthcare
1.3.4 Retail
1.3.5 Manufacturing
1.3.6 Public Sector
1.3.7 Others
1.4 Assumptions and Limitations
1.5 Study Objectives
1.6 Years Considered
2 Executive Summary
2.1 Global Machine Learning Operations (MLOps) Market Size Estimates and Forecasts
2.2 Machine Learning Operations (MLOps) Market Size by Region: 2023 Versus 2030
2.2.1 Global Machine Learning Operations (MLOps) Revenue by Region: 2019-2024
2.2.2 Global Machine Learning Operations (MLOps) Revenue Forecast by Region (2025-2030)
2.2.3 Global Machine Learning Operations (MLOps) Revenue Market Share by Region (2019-2030)
3 Global Machine Learning Operations (MLOps) by Company
3.1 Global Machine Learning Operations (MLOps) Revenue by Company (2019-2024)
3.2 Global Machine Learning Operations (MLOps) Revenue Share by Company (2019-2024)
3.3 Competitive Landscape
3.3.1 Key Machine Learning Operations (MLOps) Companies around the World: Ranking by Revenue
3.3.2 Global Machine Learning Operations (MLOps) Market Concentration Ratio (CR5 and HHI) & (2019-2024)
3.3.3 Global Machine Learning Operations (MLOps) Market Share by Company Type (Tier 1, Tier 2 and Tier 3)
3.4 Global Machine Learning Operations (MLOps) Companies Headquarters & Product Type
3.4.1 Machine Learning Operations (MLOps) Companies Headquarters
3.4.2 Global Machine Learning Operations (MLOps) Companies Product & Service
3.4.3 Date of International Companies Enter into Machine Learning Operations (MLOps) Market
3.5 Global Machine Learning Operations (MLOps) Mergers & Acquisitions, Expansion Plans
4 Company Profiles
4.1 IBM
4.1.1 IBM Company Information
4.1.2 IBM Description, Business Overview
4.1.3 IBM Machine Learning Operations (MLOps) Products Offered
4.1.4 IBM Machine Learning Operations (MLOps) Revenue and Gross Margin (2019-2024)
4.1.5 IBM Machine Learning Operations (MLOps) Revenue by Product in 2023
4.1.6 IBM Machine Learning Operations (MLOps) Revenue by Application in 2023
4.1.7 IBM Machine Learning Operations (MLOps) Revenue by Geographic Area in 2023
4.1.8 IBM Recent Developments
4.2 DataRobot
4.2.1 DataRobot Company Information
4.2.2 DataRobot Description, Business Overview
4.2.3 DataRobot Machine Learning Operations (MLOps) Products Offered
4.2.4 DataRobot Machine Learning Operations (MLOps) Revenue and Gross Margin (2019-2024)
4.2.5 DataRobot Machine Learning Operations (MLOps) Revenue by Product in 2023
4.2.6 DataRobot Machine Learning Operations (MLOps) Revenue by Application in 2023
4.2.7 DataRobot Machine Learning Operations (MLOps) Revenue by Geographic Area in 2023
4.2.8 DataRobot Recent Developments
4.3 SAS
4.3.1 SAS Company Information
4.3.2 SAS Description, Business Overview
4.3.3 SAS Machine Learning Operations (MLOps) Products Offered
4.3.4 SAS Machine Learning Operations (MLOps) Revenue and Gross Margin (2019-2024)
4.3.5 SAS Machine Learning Operations (MLOps) Revenue by Product in 2023
4.3.6 SAS Machine Learning Operations (MLOps) Revenue by Application in 2023
4.3.7 SAS Machine Learning Operations (MLOps) Revenue by Geographic Area in 2023
4.3.8 SAS Recent Developments
4.4 Microsoft
4.4.1 Microsoft Company Information
4.4.2 Microsoft Description, Business Overview
4.4.3 Microsoft Machine Learning Operations (MLOps) Products Offered
4.4.4 Microsoft Machine Learning Operations (MLOps) Revenue and Gross Margin (2019-2024)
4.4.5 Microsoft Machine Learning Operations (MLOps) Revenue by Product in 2023
4.4.6 Microsoft Machine Learning Operations (MLOps) Revenue by Application in 2023
4.4.7 Microsoft Machine Learning Operations (MLOps) Revenue by Geographic Area in 2023
4.4.8 Microsoft Recent Developments
4.5 Amazon
4.5.1 Amazon Company Information
4.5.2 Amazon Description, Business Overview
4.5.3 Amazon Machine Learning Operations (MLOps) Products Offered
4.5.4 Amazon Machine Learning Operations (MLOps) Revenue and Gross Margin (2019-2024)
4.5.5 Amazon Machine Learning Operations (MLOps) Revenue by Product in 2023
4.5.6 Amazon Machine Learning Operations (MLOps) Revenue by Application in 2023
4.5.7 Amazon Machine Learning Operations (MLOps) Revenue by Geographic Area in 2023
4.5.8 Amazon Recent Developments
4.6 Google
4.6.1 Google Company Information
4.6.2 Google Description, Business Overview
4.6.3 Google Machine Learning Operations (MLOps) Products Offered
4.6.4 Google Machine Learning Operations (MLOps) Revenue and Gross Margin (2019-2024)
4.6.5 Google Machine Learning Operations (MLOps) Revenue by Product in 2023
4.6.6 Google Machine Learning Operations (MLOps) Revenue by Application in 2023
4.6.7 Google Machine Learning Operations (MLOps) Revenue by Geographic Area in 2023
4.6.8 Google Recent Development
4.7 Dataiku
4.7.1 Dataiku Company Information
4.7.2 Dataiku Description, Business Overview
4.7.3 Dataiku Machine Learning Operations (MLOps) Products Offered
4.7.4 Dataiku Machine Learning Operations (MLOps) Revenue and Gross Margin (2019-2024)
4.7.5 Dataiku Machine Learning Operations (MLOps) Revenue by Product in 2023
4.7.6 Dataiku Machine Learning Operations (MLOps) Revenue by Application in 2023
4.7.7 Dataiku Machine Learning Operations (MLOps) Revenue by Geographic Area in 2023
4.7.8 Dataiku Recent Development
4.8 Databricks
4.8.1 Databricks Company Information
4.8.2 Databricks Description, Business Overview
4.8.3 Databricks Machine Learning Operations (MLOps) Products Offered
4.8.4 Databricks Machine Learning Operations (MLOps) Revenue and Gross Margin (2019-2024)
4.8.5 Databricks Machine Learning Operations (MLOps) Revenue by Product in 2023
4.8.6 Databricks Machine Learning Operations (MLOps) Revenue by Application in 2023
4.8.7 Databricks Machine Learning Operations (MLOps) Revenue by Geographic Area in 2023
4.8.8 Databricks Recent Development
4.9 HPE
4.9.1 HPE Company Information
4.9.2 HPE Description, Business Overview
4.9.3 HPE Machine Learning Operations (MLOps) Products Offered
4.9.4 HPE Machine Learning Operations (MLOps) Revenue and Gross Margin (2019-2024)
4.9.5 HPE Machine Learning Operations (MLOps) Revenue by Product in 2023
4.9.6 HPE Machine Learning Operations (MLOps) Revenue by Application in 2023
4.9.7 HPE Machine Learning Operations (MLOps) Revenue by Geographic Area in 2023
4.9.8 HPE Recent Development
4.10 Lguazio
4.10.1 Lguazio Company Information
4.10.2 Lguazio Description, Business Overview
4.10.3 Lguazio Machine Learning Operations (MLOps) Products Offered
4.10.4 Lguazio Machine Learning Operations (MLOps) Revenue and Gross Margin (2019-2024)
4.10.5 Lguazio Machine Learning Operations (MLOps) Revenue by Product in 2023
4.10.6 Lguazio Machine Learning Operations (MLOps) Revenue by Application in 2023
4.10.7 Lguazio Machine Learning Operations (MLOps) Revenue by Geographic Area in 2023
4.10.8 Lguazio Recent Development
4.11 ClearML
4.11.1 ClearML Company Information
4.11.2 ClearML Description, Business Overview
4.11.3 ClearML Machine Learning Operations (MLOps) Products Offered
4.11.4 ClearML Machine Learning Operations (MLOps) Revenue and Gross Margin (2019-2024)
4.11.5 ClearML Machine Learning Operations (MLOps) Revenue by Product in 2023
4.11.6 ClearML Machine Learning Operations (MLOps) Revenue by Application in 2023
4.11.7 ClearML Machine Learning Operations (MLOps) Revenue by Geographic Area in 2023
4.11.8 ClearML Recent Development
4.12 Modzy
4.12.1 Modzy Company Information
4.12.2 Modzy Description, Business Overview
4.12.3 Modzy Machine Learning Operations (MLOps) Products Offered
4.12.4 Modzy Machine Learning Operations (MLOps) Revenue and Gross Margin (2019-2024)
4.12.5 Modzy Machine Learning Operations (MLOps) Revenue by Product in 2023
4.12.6 Modzy Machine Learning Operations (MLOps) Revenue by Application in 2023
4.12.7 Modzy Machine Learning Operations (MLOps) Revenue by Geographic Area in 2023
4.12.8 Modzy Recent Development
4.13 Comet
4.13.1 Comet Company Information
4.13.2 Comet Description, Business Overview
4.13.3 Comet Machine Learning Operations (MLOps) Products Offered
4.13.4 Comet Machine Learning Operations (MLOps) Revenue and Gross Margin (2019-2024)
4.13.5 Comet Machine Learning Operations (MLOps) Revenue by Product in 2023
4.13.6 Comet Machine Learning Operations (MLOps) Revenue by Application in 2023
4.13.7 Comet Machine Learning Operations (MLOps) Revenue by Geographic Area in 2023
4.13.8 Comet Recent Development
4.14 Cloudera
4.14.1 Cloudera Company Information
4.14.2 Cloudera Description, Business Overview
4.14.3 Cloudera Machine Learning Operations (MLOps) Products Offered
4.14.4 Cloudera Machine Learning Operations (MLOps) Revenue and Gross Margin (2019-2024)
4.14.5 Cloudera Machine Learning Operations (MLOps) Revenue by Product in 2023
4.14.6 Cloudera Machine Learning Operations (MLOps) Revenue by Application in 2023
4.14.7 Cloudera Machine Learning Operations (MLOps) Revenue by Geographic Area in 2023
4.14.8 Cloudera Recent Development
4.15 Paperpace
4.15.1 Paperpace Company Information
4.15.2 Paperpace Description, Business Overview
4.15.3 Paperpace Machine Learning Operations (MLOps) Products Offered
4.15.4 Paperpace Machine Learning Operations (MLOps) Revenue and Gross Margin (2019-2024)
4.15.5 Paperpace Machine Learning Operations (MLOps) Revenue by Product in 2023
4.15.6 Paperpace Machine Learning Operations (MLOps) Revenue by Application in 2023
4.15.7 Paperpace Machine Learning Operations (MLOps) Revenue by Geographic Area in 2023
4.15.8 Paperpace Recent Development
4.16 Valohai
4.16.1 Valohai Company Information
4.16.2 Valohai Description, Business Overview
4.16.3 Valohai Machine Learning Operations (MLOps) Products Offered
4.16.4 Valohai Machine Learning Operations (MLOps) Revenue and Gross Margin (2019-2024)
4.16.5 Valohai Machine Learning Operations (MLOps) Revenue by Product in 2023
4.16.6 Valohai Machine Learning Operations (MLOps) Revenue by Application in 2023
4.16.7 Valohai Machine Learning Operations (MLOps) Revenue by Geographic Area in 2023
4.16.8 Valohai Recent Development
5 Breakdown Data by Type
5.1 Global Machine Learning Operations (MLOps) Revenue by Type (2019-2024)
5.2 Global Machine Learning Operations (MLOps) Revenue Forecast by Type (2025-2030)
5.3 Machine Learning Operations (MLOps) Revenue Market Share by Type (2019-2030)
6 Breakdown Data by Application
6.1 Global Machine Learning Operations (MLOps) Revenue by Application (2019-2024)
6.2 Global Machine Learning Operations (MLOps) Revenue Forecast by Application (2025-2030)
6.3 Machine Learning Operations (MLOps) Revenue Market Share by Application (2019-2030)
7 North America
7.1 North America Machine Learning Operations (MLOps) Market Size YoY Growth 2019-2030
7.2 North America Machine Learning Operations (MLOps) Market Facts & Figures by Country (2019-2030)
7.3 North America Machine Learning Operations (MLOps) Revenue by Type (2019-2024)
7.4 North America Machine Learning Operations (MLOps) Revenue by Application (2019-2024)
8 Asia-Pacific
8.1 Asia-Pacific Machine Learning Operations (MLOps) Market Size YoY Growth 2019-2030
8.2 Asia-Pacific Machine Learning Operations (MLOps) Market Facts & Figures by Region (2019-2030)
8.3 Asia-Pacific Machine Learning Operations (MLOps) Revenue by Type (2019-2024)
8.4 Asia-Pacific Machine Learning Operations (MLOps) Revenue by Application (2019-2024)
9 Europe
9.1 Europe Machine Learning Operations (MLOps) Market Size YoY Growth 2019-2030
9.2 Europe Machine Learning Operations (MLOps) Market Facts & Figures by Country (2019-2030)
9.3 Europe Machine Learning Operations (MLOps) Revenue by Type (2019-2024)
9.4 Europe Machine Learning Operations (MLOps) Revenue by Application (2019-2024)
10 Latin America
10.1 Latin America Machine Learning Operations (MLOps) Market Size YoY Growth 2019-2030
10.2 Latin America Machine Learning Operations (MLOps) Market Facts & Figures by Country (2019-2030)
10.3 Latin America Machine Learning Operations (MLOps) Revenue by Type (2019-2024)
10.4 Latin America Machine Learning Operations (MLOps) Revenue by Application (2019-2024)
11 Middle East and Africa
11.1 Middle East and Africa Machine Learning Operations (MLOps) Market Size YoY Growth 2019-2030
11.2 Middle East and Africa Machine Learning Operations (MLOps) Market Facts & Figures by Country (2019-2030)
11.3 Middle East and Africa Machine Learning Operations (MLOps) Revenue by Type (2019-2024)
11.4 Middle East and Africa Machine Learning Operations (MLOps) Revenue by Application (2019-2024)
12 Supply Chain and Sales Channel Analysis
12.1 Machine Learning Operations (MLOps) Supply Chain Analysis
12.2 Machine Learning Operations (MLOps) Key Raw Materials and Upstream Suppliers
12.3 Machine Learning Operations (MLOps) Clients Analysis
12.4 Machine Learning Operations (MLOps) Sales Channel and Sales Model Analysis
12.4.1 Machine Learning Operations (MLOps) Distribution Channel Analysis: Indirect Sales VS Direct Sales
12.4.2 Machine Learning Operations (MLOps) Distribution Channel Analysis: Online Sales VS Offline Sales
12.4.3 Machine Learning Operations (MLOps) Distributors
13 Market Dynamics
13.1 Machine Learning Operations (MLOps) Industry Trends
13.2 Machine Learning Operations (MLOps) Market Drivers
13.3 Machine Learning Operations (MLOps) Market Challenges
13.4 Machine Learning Operations (MLOps) Market Restraints
14 Research Findings and Conclusion
15 Appendix
15.1 Research Methodology
15.1.1 Methodology/Research Approach
15.1.2 Data Source
15.2 Author Details
15.3 Disclaimer
IBM
DataRobot
SAS
Microsoft
Amazon
Google
Dataiku
Databricks
HPE
Lguazio
ClearML
Modzy
Comet
Cloudera
Paperpace
Valohai
听
听
*If Applicable.
