The global Machine Learning Operations (MLOps) market size was valued at USD 561.3 million in 2023 and is forecast to a readjusted size of USD 5903.6 million by 2030 with a CAGR of 40.0% during review period.
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 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.
The report includes an overview of the development of the Machine Learning Operations (MLOps) industry chain, the market status of BFSI (On-premise, Cloud), Healthcare (On-premise, Cloud), and key enterprises in developed and developing market, and analysed the cutting-edge technology, patent, hot applications and market trends of Machine Learning Operations (MLOps).
Regionally, the report analyzes the Machine Learning Operations (MLOps) markets in key regions. North America and Europe are experiencing steady growth, driven by government initiatives and increasing consumer awareness. Asia-Pacific, particularly China, leads the global Machine Learning Operations (MLOps) market, with robust domestic demand, supportive policies, and a strong manufacturing base.
Key Features:
The report presents comprehensive understanding of the Machine Learning Operations (MLOps) market. It provides a holistic view of the industry, as well as detailed insights into individual components and stakeholders. The report analysis market dynamics, trends, challenges, and opportunities within the Machine Learning Operations (MLOps) industry.
The report involves analyzing the market at a macro level:
Market Sizing and Segmentation: Report collect data on the overall market size, including the revenue generated, and market share of different by Type (e.g., On-premise, Cloud).
Industry Analysis: Report analyse the broader industry trends, such as government policies and regulations, technological advancements, consumer preferences, and market dynamics. This analysis helps in understanding the key drivers and challenges influencing the Machine Learning Operations (MLOps) market.
Regional Analysis: The report involves examining the Machine Learning Operations (MLOps) market at a regional or national level. Report analyses regional factors such as government incentives, infrastructure development, economic conditions, and consumer behaviour to identify variations and opportunities within different markets.
Market Projections: Report covers the gathered data and analysis to make future projections and forecasts for the Machine Learning Operations (MLOps) market. This may include estimating market growth rates, predicting market demand, and identifying emerging trends.
The report also involves a more granular approach to Machine Learning Operations (MLOps):
Company Analysis: Report covers individual Machine Learning Operations (MLOps) players, suppliers, and other relevant industry players. This analysis includes studying their financial performance, market positioning, product portfolios, partnerships, and strategies.
Consumer Analysis: Report covers data on consumer behaviour, preferences, and attitudes towards Machine Learning Operations (MLOps) This may involve surveys, interviews, and analysis of consumer reviews and feedback from different by Application (BFSI, Healthcare).
Technology Analysis: Report covers specific technologies relevant to Machine Learning Operations (MLOps). It assesses the current state, advancements, and potential future developments in Machine Learning Operations (MLOps) areas.
Competitive Landscape: By analyzing individual companies, suppliers, and consumers, the report present insights into the competitive landscape of the Machine Learning Operations (MLOps) market. This analysis helps understand market share, competitive advantages, and potential areas for differentiation among industry players.
Market Validation: The report involves validating findings and projections through primary research, such as surveys, interviews, and focus groups.
Market Segmentation
Machine Learning Operations (MLOps) market is split by Type and by Application. For the period 2019-2030, the growth among segments provides accurate calculations and forecasts for consumption value by Type, and by Application in terms of value.
Market segment by Type
On-premise
Cloud
Others
Market segment by Application
BFSI
Healthcare
Retail
Manufacturing
Public Sector
Others
Market segment by players, this report covers
IBM
DataRobot
SAS
Microsoft
Amazon
Google
Dataiku
Databricks
HPE
Lguazio
ClearML
Modzy
Comet
Cloudera
Paperpace
Valohai
Market segment by regions, regional analysis covers
North America (United States, Canada, and Mexico)
Europe (Germany, France, UK, Russia, Italy, and Rest of Europe)
Asia-Pacific (China, Japan, South Korea, India, Southeast Asia, Australia and Rest of Asia-Pacific)
South America (Brazil, Argentina and Rest of South America)
Middle East & Africa (Turkey, Saudi Arabia, UAE, Rest of Middle East & Africa)
The content of the study subjects, includes a total of 13 chapters:
Chapter 1, to describe Machine Learning Operations (MLOps) product scope, market overview, market estimation caveats and base year.
Chapter 2, to profile the top players of Machine Learning Operations (MLOps), with revenue, gross margin and global market share of Machine Learning Operations (MLOps) from 2019 to 2024.
Chapter 3, the Machine Learning Operations (MLOps) competitive situation, revenue and global market share of top players are analyzed emphatically by landscape contrast.
Chapter 4 and 5, to segment the market size by Type and application, with consumption value and growth rate by Type, application, from 2019 to 2030.
Chapter 6, 7, 8, 9, and 10, to break the market size data at the country level, with revenue and market share for key countries in the world, from 2019 to 2024.and Machine Learning Operations (MLOps) market forecast, by regions, type and application, with consumption value, from 2025 to 2030.
Chapter 11, market dynamics, drivers, restraints, trends and Porters Five Forces analysis.
Chapter 12, the key raw materials and key suppliers, and industry chain of Machine Learning Operations (MLOps).
Chapter 13, to describe Machine Learning Operations (MLOps) research findings and conclusion.
Please Note - This is an on demand report and will be delivered in 2 business days (48 Hours) post payment.
1 Market Overview
1.1 Product Overview and Scope of Machine Learning Operations (MLOps)
1.2 Market Estimation Caveats and Base Year
1.3 Classification of Machine Learning Operations (MLOps) by Type
1.3.1 Overview: Global Machine Learning Operations (MLOps) Market Size by Type: 2019 Versus 2023 Versus 2030
1.3.2 Global Machine Learning Operations (MLOps) Consumption Value Market Share by Type in 2023
1.3.3 On-premise
1.3.4 Cloud
1.3.5 Others
1.4 Global Machine Learning Operations (MLOps) Market by Application
1.4.1 Overview: Global Machine Learning Operations (MLOps) Market Size by Application: 2019 Versus 2023 Versus 2030
1.4.2 BFSI
1.4.3 Healthcare
1.4.4 Retail
1.4.5 Manufacturing
1.4.6 Public Sector
1.4.7 Others
1.5 Global Machine Learning Operations (MLOps) Market Size & Forecast
1.6 Global Machine Learning Operations (MLOps) Market Size and Forecast by Region
1.6.1 Global Machine Learning Operations (MLOps) Market Size by Region: 2019 VS 2023 VS 2030
1.6.2 Global Machine Learning Operations (MLOps) Market Size by Region, (2019-2030)
1.6.3 North America Machine Learning Operations (MLOps) Market Size and Prospect (2019-2030)
1.6.4 Europe Machine Learning Operations (MLOps) Market Size and Prospect (2019-2030)
1.6.5 Asia-Pacific Machine Learning Operations (MLOps) Market Size and Prospect (2019-2030)
1.6.6 South America Machine Learning Operations (MLOps) Market Size and Prospect (2019-2030)
1.6.7 Middle East and Africa Machine Learning Operations (MLOps) Market Size and Prospect (2019-2030)
2 Company Profiles
2.1 IBM
2.1.1 IBM Details
2.1.2 IBM Major Business
2.1.3 IBM Machine Learning Operations (MLOps) Product and Solutions
2.1.4 IBM Machine Learning Operations (MLOps) Revenue, Gross Margin and Market Share (2019-2024)
2.1.5 IBM Recent Developments and Future Plans
2.2 DataRobot
2.2.1 DataRobot Details
2.2.2 DataRobot Major Business
2.2.3 DataRobot Machine Learning Operations (MLOps) Product and Solutions
2.2.4 DataRobot Machine Learning Operations (MLOps) Revenue, Gross Margin and Market Share (2019-2024)
2.2.5 DataRobot Recent Developments and Future Plans
2.3 SAS
2.3.1 SAS Details
2.3.2 SAS Major Business
2.3.3 SAS Machine Learning Operations (MLOps) Product and Solutions
2.3.4 SAS Machine Learning Operations (MLOps) Revenue, Gross Margin and Market Share (2019-2024)
2.3.5 SAS Recent Developments and Future Plans
2.4 Microsoft
2.4.1 Microsoft Details
2.4.2 Microsoft Major Business
2.4.3 Microsoft Machine Learning Operations (MLOps) Product and Solutions
2.4.4 Microsoft Machine Learning Operations (MLOps) Revenue, Gross Margin and Market Share (2019-2024)
2.4.5 Microsoft Recent Developments and Future Plans
2.5 Amazon
2.5.1 Amazon Details
2.5.2 Amazon Major Business
2.5.3 Amazon Machine Learning Operations (MLOps) Product and Solutions
2.5.4 Amazon Machine Learning Operations (MLOps) Revenue, Gross Margin and Market Share (2019-2024)
2.5.5 Amazon Recent Developments and Future Plans
2.6 Google
2.6.1 Google Details
2.6.2 Google Major Business
2.6.3 Google Machine Learning Operations (MLOps) Product and Solutions
2.6.4 Google Machine Learning Operations (MLOps) Revenue, Gross Margin and Market Share (2019-2024)
2.6.5 Google Recent Developments and Future Plans
2.7 Dataiku
2.7.1 Dataiku Details
2.7.2 Dataiku Major Business
2.7.3 Dataiku Machine Learning Operations (MLOps) Product and Solutions
2.7.4 Dataiku Machine Learning Operations (MLOps) Revenue, Gross Margin and Market Share (2019-2024)
2.7.5 Dataiku Recent Developments and Future Plans
2.8 Databricks
2.8.1 Databricks Details
2.8.2 Databricks Major Business
2.8.3 Databricks Machine Learning Operations (MLOps) Product and Solutions
2.8.4 Databricks Machine Learning Operations (MLOps) Revenue, Gross Margin and Market Share (2019-2024)
2.8.5 Databricks Recent Developments and Future Plans
2.9 HPE
2.9.1 HPE Details
2.9.2 HPE Major Business
2.9.3 HPE Machine Learning Operations (MLOps) Product and Solutions
2.9.4 HPE Machine Learning Operations (MLOps) Revenue, Gross Margin and Market Share (2019-2024)
2.9.5 HPE Recent Developments and Future Plans
2.10 Lguazio
2.10.1 Lguazio Details
2.10.2 Lguazio Major Business
2.10.3 Lguazio Machine Learning Operations (MLOps) Product and Solutions
2.10.4 Lguazio Machine Learning Operations (MLOps) Revenue, Gross Margin and Market Share (2019-2024)
2.10.5 Lguazio Recent Developments and Future Plans
2.11 ClearML
2.11.1 ClearML Details
2.11.2 ClearML Major Business
2.11.3 ClearML Machine Learning Operations (MLOps) Product and Solutions
2.11.4 ClearML Machine Learning Operations (MLOps) Revenue, Gross Margin and Market Share (2019-2024)
2.11.5 ClearML Recent Developments and Future Plans
2.12 Modzy
2.12.1 Modzy Details
2.12.2 Modzy Major Business
2.12.3 Modzy Machine Learning Operations (MLOps) Product and Solutions
2.12.4 Modzy Machine Learning Operations (MLOps) Revenue, Gross Margin and Market Share (2019-2024)
2.12.5 Modzy Recent Developments and Future Plans
2.13 Comet
2.13.1 Comet Details
2.13.2 Comet Major Business
2.13.3 Comet Machine Learning Operations (MLOps) Product and Solutions
2.13.4 Comet Machine Learning Operations (MLOps) Revenue, Gross Margin and Market Share (2019-2024)
2.13.5 Comet Recent Developments and Future Plans
2.14 Cloudera
2.14.1 Cloudera Details
2.14.2 Cloudera Major Business
2.14.3 Cloudera Machine Learning Operations (MLOps) Product and Solutions
2.14.4 Cloudera Machine Learning Operations (MLOps) Revenue, Gross Margin and Market Share (2019-2024)
2.14.5 Cloudera Recent Developments and Future Plans
2.15 Paperpace
2.15.1 Paperpace Details
2.15.2 Paperpace Major Business
2.15.3 Paperpace Machine Learning Operations (MLOps) Product and Solutions
2.15.4 Paperpace Machine Learning Operations (MLOps) Revenue, Gross Margin and Market Share (2019-2024)
2.15.5 Paperpace Recent Developments and Future Plans
2.16 Valohai
2.16.1 Valohai Details
2.16.2 Valohai Major Business
2.16.3 Valohai Machine Learning Operations (MLOps) Product and Solutions
2.16.4 Valohai Machine Learning Operations (MLOps) Revenue, Gross Margin and Market Share (2019-2024)
2.16.5 Valohai Recent Developments and Future Plans
3 Market Competition, by Players
3.1 Global Machine Learning Operations (MLOps) Revenue and Share by Players (2019-2024)
3.2 Market Share Analysis (2023)
3.2.1 Market Share of Machine Learning Operations (MLOps) by Company Revenue
3.2.2 Top 3 Machine Learning Operations (MLOps) Players Market Share in 2023
3.2.3 Top 6 Machine Learning Operations (MLOps) Players Market Share in 2023
3.3 Machine Learning Operations (MLOps) Market: Overall Company Footprint Analysis
3.3.1 Machine Learning Operations (MLOps) Market: Region Footprint
3.3.2 Machine Learning Operations (MLOps) Market: Company Product Type Footprint
3.3.3 Machine Learning Operations (MLOps) Market: Company Product Application Footprint
3.4 New Market Entrants and Barriers to Market Entry
3.5 Mergers, Acquisition, Agreements, and Collaborations
4 Market Size Segment by Type
4.1 Global Machine Learning Operations (MLOps) Consumption Value and Market Share by Type (2019-2024)
4.2 Global Machine Learning Operations (MLOps) Market Forecast by Type (2025-2030)
5 Market Size Segment by Application
5.1 Global Machine Learning Operations (MLOps) Consumption Value Market Share by Application (2019-2024)
5.2 Global Machine Learning Operations (MLOps) Market Forecast by Application (2025-2030)
6 North America
6.1 North America Machine Learning Operations (MLOps) Consumption Value by Type (2019-2030)
6.2 North America Machine Learning Operations (MLOps) Consumption Value by Application (2019-2030)
6.3 North America Machine Learning Operations (MLOps) Market Size by Country
6.3.1 North America Machine Learning Operations (MLOps) Consumption Value by Country (2019-2030)
6.3.2 United States Machine Learning Operations (MLOps) Market Size and Forecast (2019-2030)
6.3.3 Canada Machine Learning Operations (MLOps) Market Size and Forecast (2019-2030)
6.3.4 Mexico Machine Learning Operations (MLOps) Market Size and Forecast (2019-2030)
7 Europe
7.1 Europe Machine Learning Operations (MLOps) Consumption Value by Type (2019-2030)
7.2 Europe Machine Learning Operations (MLOps) Consumption Value by Application (2019-2030)
7.3 Europe Machine Learning Operations (MLOps) Market Size by Country
7.3.1 Europe Machine Learning Operations (MLOps) Consumption Value by Country (2019-2030)
7.3.2 Germany Machine Learning Operations (MLOps) Market Size and Forecast (2019-2030)
7.3.3 France Machine Learning Operations (MLOps) Market Size and Forecast (2019-2030)
7.3.4 United Kingdom Machine Learning Operations (MLOps) Market Size and Forecast (2019-2030)
7.3.5 Russia Machine Learning Operations (MLOps) Market Size and Forecast (2019-2030)
7.3.6 Italy Machine Learning Operations (MLOps) Market Size and Forecast (2019-2030)
8 Asia-Pacific
8.1 Asia-Pacific Machine Learning Operations (MLOps) Consumption Value by Type (2019-2030)
8.2 Asia-Pacific Machine Learning Operations (MLOps) Consumption Value by Application (2019-2030)
8.3 Asia-Pacific Machine Learning Operations (MLOps) Market Size by Region
8.3.1 Asia-Pacific Machine Learning Operations (MLOps) Consumption Value by Region (2019-2030)
8.3.2 China Machine Learning Operations (MLOps) Market Size and Forecast (2019-2030)
8.3.3 Japan Machine Learning Operations (MLOps) Market Size and Forecast (2019-2030)
8.3.4 South Korea Machine Learning Operations (MLOps) Market Size and Forecast (2019-2030)
8.3.5 India Machine Learning Operations (MLOps) Market Size and Forecast (2019-2030)
8.3.6 Southeast Asia Machine Learning Operations (MLOps) Market Size and Forecast (2019-2030)
8.3.7 Australia Machine Learning Operations (MLOps) Market Size and Forecast (2019-2030)
9 South America
9.1 South America Machine Learning Operations (MLOps) Consumption Value by Type (2019-2030)
9.2 South America Machine Learning Operations (MLOps) Consumption Value by Application (2019-2030)
9.3 South America Machine Learning Operations (MLOps) Market Size by Country
9.3.1 South America Machine Learning Operations (MLOps) Consumption Value by Country (2019-2030)
9.3.2 Brazil Machine Learning Operations (MLOps) Market Size and Forecast (2019-2030)
9.3.3 Argentina Machine Learning Operations (MLOps) Market Size and Forecast (2019-2030)
10 Middle East & Africa
10.1 Middle East & Africa Machine Learning Operations (MLOps) Consumption Value by Type (2019-2030)
10.2 Middle East & Africa Machine Learning Operations (MLOps) Consumption Value by Application (2019-2030)
10.3 Middle East & Africa Machine Learning Operations (MLOps) Market Size by Country
10.3.1 Middle East & Africa Machine Learning Operations (MLOps) Consumption Value by Country (2019-2030)
10.3.2 Turkey Machine Learning Operations (MLOps) Market Size and Forecast (2019-2030)
10.3.3 Saudi Arabia Machine Learning Operations (MLOps) Market Size and Forecast (2019-2030)
10.3.4 UAE Machine Learning Operations (MLOps) Market Size and Forecast (2019-2030)
11 Market Dynamics
11.1 Machine Learning Operations (MLOps) Market Drivers
11.2 Machine Learning Operations (MLOps) Market Restraints
11.3 Machine Learning Operations (MLOps) Trends Analysis
11.4 Porters Five Forces Analysis
11.4.1 Threat of New Entrants
11.4.2 Bargaining Power of Suppliers
11.4.3 Bargaining Power of Buyers
11.4.4 Threat of Substitutes
11.4.5 Competitive Rivalry
12 Industry Chain Analysis
12.1 Machine Learning Operations (MLOps) Industry Chain
12.2 Machine Learning Operations (MLOps) Upstream Analysis
12.3 Machine Learning Operations (MLOps) Midstream Analysis
12.4 Machine Learning Operations (MLOps) Downstream Analysis
13 Research Findings and Conclusion
14 Appendix
14.1 Methodology
14.2 Research Process and Data Source
14.3 Disclaimer
IBM
DataRobot
SAS
Microsoft
Amazon
Google
Dataiku
Databricks
HPE
Lguazio
ClearML
Modzy
Comet
Cloudera
Paperpace
Valohai
听
听
*If Applicable.