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.
Market Analysis and Insights: Global Machine Learning Operations (MLOps) Market
The global Machine Learning Operations (MLOps) market is projected to grow from US$ 1117.7 million in 2024 to US$ 9066.7 million by 2030, at a Compound Annual Growth Rate (CAGR) of 41.8% during the forecast period.
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 Covers:
This report presents an overview of global market for Machine Learning Operations (MLOps) market size. Analyses of the global market trends, with historic market revenue data for 2019 - 2023, estimates for 2024, and projections of CAGR through 2030.
This report researches the key producers of Machine Learning Operations (MLOps), also provides the revenue of main regions and countries. Highlights of the upcoming market potential for Machine Learning Operations (MLOps), and key regions/countries of focus to forecast this market into various segments and sub-segments. Country specific data and market value analysis for the U.S., Canada, Mexico, Brazil, China, Japan, South Korea, Southeast Asia, India, Germany, the U.K., Italy, Middle East, Africa, and Other Countries.
This report focuses on the Machine Learning Operations (MLOps) revenue, market share and industry ranking of main companies, data from 2019 to 2024. Identification of the major stakeholders in the global Machine Learning Operations (MLOps) market, and analysis of their competitive landscape and market positioning based on recent developments and segmental revenues. This report will help stakeholders to understand the competitive landscape and gain more insights and position their businesses and market strategies in a better way.
This report analyzes the segments data by Type and by Application, revenue, and growth rate, from 2019 to 2030. Evaluation and forecast the market size for Machine Learning Operations (MLOps) revenue, projected growth trends, production technology, application and end-user industry.
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
UK
Italy
Russia
Nordic Countries
Rest of Europe
China
Asia (excluding China)
Japan
South Korea
China Taiwan
Southeast Asia
India
Latin America, Middle East & Africa
Brazil
Mexico
Turkey
Israel
GCC Countries
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. It offers a high-level view of the current state of the market and its likely evolution in the short to mid-term, and long term.
Chapter 2: Revenue of Machine Learning Operations (MLOps) in global and regional level. It provides a quantitative analysis of the market size and development potential of each region and its main countries and introduces the market development, future development prospects, market space, and capacity of each country in the world. This section also introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by companies in the industry, and the analysis of relevant policies in the industry.
Chapter 3: Detailed analysis of Machine Learning Operations (MLOps) companies鈥� competitive landscape, revenue, market share and industry ranking, latest development plan, merger, and acquisition information, etc.
Chapter 4: 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 5: 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 6: North America (US & Canada) by Type, by Application and by country, revenue for each segment.
Chapter 7: Europe by Type, by Application and by country, revenue for each segment.
Chapter 8: China by Type, and by Application, revenue for each segment.
Chapter 9: Asia (excluding China) by Type, by Application and by region, revenue for each segment.
Chapter 10: Middle East, Africa, and Latin America by Type, by Application and by country, revenue for each segment.
Chapter 11: 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 12: Analyst's Viewpoints/Conclusions
Please Note - This is an on demand report and will be delivered in 2 business days (48 hours) post payment.
1 Report Overview
1.1 Study Scope
1.2 Market Analysis 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 Global Growth Trends
2.1 Global Machine Learning Operations (MLOps) Market Perspective (2019-2030)
2.2 Global Machine Learning Operations (MLOps) Growth Trends by Region
2.2.1 Machine Learning Operations (MLOps) Market Size by Region: 2019 VS 2023 VS 2030
2.2.2 Machine Learning Operations (MLOps) Historic Market Size by Region (2019-2024)
2.2.3 Machine Learning Operations (MLOps) Forecasted Market Size by Region (2025-2030)
2.3 Machine Learning Operations (MLOps) Market Dynamics
2.3.1 Machine Learning Operations (MLOps) Industry Trends
2.3.2 Machine Learning Operations (MLOps) Market Drivers
2.3.3 Machine Learning Operations (MLOps) Market Challenges
2.3.4 Machine Learning Operations (MLOps) Market Restraints
3 Competition Landscape by Key Players
3.1 Global Revenue Machine Learning Operations (MLOps) by Players
3.1.1 Global Machine Learning Operations (MLOps) Revenue by Players (2019-2024)
3.1.2 Global Machine Learning Operations (MLOps) Revenue Market Share by Players (2019-2024)
3.2 Global Machine Learning Operations (MLOps) Market Share by Company Type (Tier 1, Tier 2, and Tier 3)
3.3 Global Key Players of Machine Learning Operations (MLOps), Ranking by Revenue, 2022 VS 2023 VS 2024
3.4 Global Machine Learning Operations (MLOps) Market Concentration Ratio
3.4.1 Global Machine Learning Operations (MLOps) Market Concentration Ratio (CR5 and HHI)
3.4.2 Global Top 10 and Top 5 Companies by Machine Learning Operations (MLOps) Revenue in 2023
3.5 Global Key Players of Machine Learning Operations (MLOps) Head office and Area Served
3.6 Global Key Players of Machine Learning Operations (MLOps), Product and Application
3.7 Global Key Players of Machine Learning Operations (MLOps), Date of Enter into This Industry
3.8 Mergers & Acquisitions, Expansion Plans
4 Machine Learning Operations (MLOps) Breakdown Data by Type
4.1 Global Machine Learning Operations (MLOps) Historic Market Size by Type (2019-2024)
4.2 Global Machine Learning Operations (MLOps) Forecasted Market Size by Type (2025-2030)
5 Machine Learning Operations (MLOps) Breakdown Data by Application
5.1 Global Machine Learning Operations (MLOps) Historic Market Size by Application (2019-2024)
5.2 Global Machine Learning Operations (MLOps) Forecasted Market Size by Application (2025-2030)
6 North America
6.1 North America Machine Learning Operations (MLOps) Market Size (2019-2030)
6.2 North America Machine Learning Operations (MLOps) Market Size by Type
6.2.1 North America Machine Learning Operations (MLOps) Market Size by Type (2019-2024)
6.2.2 North America Machine Learning Operations (MLOps) Market Size by Type (2025-2030)
6.2.3 North America Machine Learning Operations (MLOps) Market Share by Type (2019-2030)
6.3 North America Machine Learning Operations (MLOps) Market Size by Application
6.3.1 North America Machine Learning Operations (MLOps) Market Size by Application (2019-2024)
6.3.2 North America Machine Learning Operations (MLOps) Market Size by Application (2025-2030)
6.3.3 North America Machine Learning Operations (MLOps) Market Share by Application (2019-2030)
6.4 North America Machine Learning Operations (MLOps) Market Size by Country
6.4.1 North America Machine Learning Operations (MLOps) Market Size by Country: 2019 VS 2023 VS 2030
6.4.2 North America Machine Learning Operations (MLOps) Market Size by Country (2019-2024)
6.4.3 North America Machine Learning Operations (MLOps) Market Size by Country (2025-2030)
6.4.4 United States
6.4.5 Canada
7 Europe
7.1 Europe Machine Learning Operations (MLOps) Market Size (2019-2030)
7.2 Europe Machine Learning Operations (MLOps) Market Size by Type
7.2.1 Europe Machine Learning Operations (MLOps) Market Size by Type (2019-2024)
7.2.2 Europe Machine Learning Operations (MLOps) Market Size by Type (2025-2030)
7.2.3 Europe Machine Learning Operations (MLOps) Market Share by Type (2019-2030)
7.3 Europe Machine Learning Operations (MLOps) Market Size by Application
7.3.1 Europe Machine Learning Operations (MLOps) Market Size by Application (2019-2024)
7.3.2 Europe Machine Learning Operations (MLOps) Market Size by Application (2025-2030)
7.3.3 Europe Machine Learning Operations (MLOps) Market Share by Application (2019-2030)
7.4 Europe Machine Learning Operations (MLOps) Market Size by Country
7.4.1 Europe Machine Learning Operations (MLOps) Market Size by Country: 2019 VS 2023 VS 2030
7.4.2 Europe Machine Learning Operations (MLOps) Market Size by Country (2019-2024)
7.4.3 Europe Machine Learning Operations (MLOps) Market Size by Country (2025-2030)
7.4.3 Germany
7.4.4 France
7.4.5 U.K.
7.4.6 Italy
7.4.7 Russia
7.4.8 Nordic Countries
8 China
8.1 China Machine Learning Operations (MLOps) Market Size (2019-2030)
8.2 China Machine Learning Operations (MLOps) Market Size by Type
8.2.1 China Machine Learning Operations (MLOps) Market Size by Type (2019-2024)
8.2.2 China Machine Learning Operations (MLOps) Market Size by Type (2025-2030)
8.2.3 China Machine Learning Operations (MLOps) Market Share by Type (2019-2030)
8.3 China Machine Learning Operations (MLOps) Market Size by Application
8.3.1 China Machine Learning Operations (MLOps) Market Size by Application (2019-2024)
8.3.2 China Machine Learning Operations (MLOps) Market Size by Application (2025-2030)
8.3.3 China Machine Learning Operations (MLOps) Market Share by Application (2019-2030)
9 Asia (excluding China)
9.1 Asia Machine Learning Operations (MLOps) Market Size (2019-2030)
9.2 Asia Machine Learning Operations (MLOps) Market Size by Type
9.2.1 Asia Machine Learning Operations (MLOps) Market Size by Type (2019-2024)
9.2.2 Asia Machine Learning Operations (MLOps) Market Size by Type (2025-2030)
9.2.3 Asia Machine Learning Operations (MLOps) Market Share by Type (2019-2030)
9.3 Asia Machine Learning Operations (MLOps) Market Size by Application
9.3.1 Asia Machine Learning Operations (MLOps) Market Size by Application (2019-2024)
9.3.2 Asia Machine Learning Operations (MLOps) Market Size by Application (2025-2030)
9.3.3 Asia Machine Learning Operations (MLOps) Market Share by Application (2019-2030)
9.4 Asia Machine Learning Operations (MLOps) Market Size by Region
9.4.1 Asia Machine Learning Operations (MLOps) Market Size by Region: 2019 VS 2023 VS 2030
9.4.2 Asia Machine Learning Operations (MLOps) Market Size by Region (2019-2024)
9.4.3 Asia Machine Learning Operations (MLOps) Market Size by Region (2025-2030)
9.4.4 Japan
9.4.5 South Korea
9.4.6 China Taiwan
9.4.7 Southeast Asia
9.4.8 India
9.4.9 Australia
10 Middle East, Africa, and Latin America
10.1 Middle East, Africa, and Latin America Machine Learning Operations (MLOps) Market Size (2019-2030)
10.2 Middle East, Africa, and Latin America Machine Learning Operations (MLOps) Market Size by Type
10.2.1 Middle East, Africa, and Latin America Machine Learning Operations (MLOps) Market Size by Type (2019-2024)
10.2.2 Middle East, Africa, and Latin America Machine Learning Operations (MLOps) Market Size by Type (2025-2030)
10.2.3 Middle East, Africa, and Latin America Machine Learning Operations (MLOps) Market Share by Type (2019-2030)
10.3 Middle East, Africa, and Latin America Machine Learning Operations (MLOps) Market Size by Application
10.3.1 Middle East, Africa, and Latin America Machine Learning Operations (MLOps) Market Size by Application (2019-2024)
10.3.2 Middle East, Africa, and Latin America Machine Learning Operations (MLOps) Market Size by Application (2025-2030)
10.3.3 Middle East, Africa, and Latin America Machine Learning Operations (MLOps) Market Share by Application (2019-2030)
10.4 Middle East, Africa, and Latin America Machine Learning Operations (MLOps) Market Size by Country
10.4.1 Middle East, Africa, and Latin America Machine Learning Operations (MLOps) Market Size by Country: 2019 VS 2023 VS 2030
10.4.2 Middle East, Africa, and Latin America Machine Learning Operations (MLOps) Market Size by Country (2019-2024)
10.4.3 Middle East, Africa, and Latin America Machine Learning Operations (MLOps) Market Size by Country (2025-2030)
10.4.4 Brazil
10.4.5 Mexico
10.4.6 Turkey
10.4.7 Saudi Arabia
10.4.8 Israel
10.4.9 GCC Countries
11 Key Players Profiles
11.1 IBM
11.1.1 IBM Company Details
11.1.2 IBM Business Overview
11.1.3 IBM Machine Learning Operations (MLOps) Introduction
11.1.4 IBM Revenue in Machine Learning Operations (MLOps) Business (2019-2024)
11.1.5 IBM Recent Developments
11.2 DataRobot
11.2.1 DataRobot Company Details
11.2.2 DataRobot Business Overview
11.2.3 DataRobot Machine Learning Operations (MLOps) Introduction
11.2.4 DataRobot Revenue in Machine Learning Operations (MLOps) Business (2019-2024)
11.2.5 DataRobot Recent Developments
11.3 SAS
11.3.1 SAS Company Details
11.3.2 SAS Business Overview
11.3.3 SAS Machine Learning Operations (MLOps) Introduction
11.3.4 SAS Revenue in Machine Learning Operations (MLOps) Business (2019-2024)
11.3.5 SAS Recent Developments
11.4 Microsoft
11.4.1 Microsoft Company Details
11.4.2 Microsoft Business Overview
11.4.3 Microsoft Machine Learning Operations (MLOps) Introduction
11.4.4 Microsoft Revenue in Machine Learning Operations (MLOps) Business (2019-2024)
11.4.5 Microsoft Recent Developments
11.5 Amazon
11.5.1 Amazon Company Details
11.5.2 Amazon Business Overview
11.5.3 Amazon Machine Learning Operations (MLOps) Introduction
11.5.4 Amazon Revenue in Machine Learning Operations (MLOps) Business (2019-2024)
11.5.5 Amazon Recent Developments
11.6 Google
11.6.1 Google Company Details
11.6.2 Google Business Overview
11.6.3 Google Machine Learning Operations (MLOps) Introduction
11.6.4 Google Revenue in Machine Learning Operations (MLOps) Business (2019-2024)
11.6.5 Google Recent Developments
11.7 Dataiku
11.7.1 Dataiku Company Details
11.7.2 Dataiku Business Overview
11.7.3 Dataiku Machine Learning Operations (MLOps) Introduction
11.7.4 Dataiku Revenue in Machine Learning Operations (MLOps) Business (2019-2024)
11.7.5 Dataiku Recent Developments
11.8 Databricks
11.8.1 Databricks Company Details
11.8.2 Databricks Business Overview
11.8.3 Databricks Machine Learning Operations (MLOps) Introduction
11.8.4 Databricks Revenue in Machine Learning Operations (MLOps) Business (2019-2024)
11.8.5 Databricks Recent Developments
11.9 HPE
11.9.1 HPE Company Details
11.9.2 HPE Business Overview
11.9.3 HPE Machine Learning Operations (MLOps) Introduction
11.9.4 HPE Revenue in Machine Learning Operations (MLOps) Business (2019-2024)
11.9.5 HPE Recent Developments
11.10 Lguazio
11.10.1 Lguazio Company Details
11.10.2 Lguazio Business Overview
11.10.3 Lguazio Machine Learning Operations (MLOps) Introduction
11.10.4 Lguazio Revenue in Machine Learning Operations (MLOps) Business (2019-2024)
11.10.5 Lguazio Recent Developments
11.11 ClearML
11.11.1 ClearML Company Details
11.11.2 ClearML Business Overview
11.11.3 ClearML Machine Learning Operations (MLOps) Introduction
11.11.4 ClearML Revenue in Machine Learning Operations (MLOps) Business (2019-2024)
11.11.5 ClearML Recent Developments
11.12 Modzy
11.12.1 Modzy Company Details
11.12.2 Modzy Business Overview
11.12.3 Modzy Machine Learning Operations (MLOps) Introduction
11.12.4 Modzy Revenue in Machine Learning Operations (MLOps) Business (2019-2024)
11.12.5 Modzy Recent Developments
11.13 Comet
11.13.1 Comet Company Details
11.13.2 Comet Business Overview
11.13.3 Comet Machine Learning Operations (MLOps) Introduction
11.13.4 Comet Revenue in Machine Learning Operations (MLOps) Business (2019-2024)
11.13.5 Comet Recent Developments
11.14 Cloudera
11.14.1 Cloudera Company Details
11.14.2 Cloudera Business Overview
11.14.3 Cloudera Machine Learning Operations (MLOps) Introduction
11.14.4 Cloudera Revenue in Machine Learning Operations (MLOps) Business (2019-2024)
11.14.5 Cloudera Recent Developments
11.15 Paperpace
11.15.1 Paperpace Company Details
11.15.2 Paperpace Business Overview
11.15.3 Paperpace Machine Learning Operations (MLOps) Introduction
11.15.4 Paperpace Revenue in Machine Learning Operations (MLOps) Business (2019-2024)
11.15.5 Paperpace Recent Developments
11.16 Valohai
11.16.1 Valohai Company Details
11.16.2 Valohai Business Overview
11.16.3 Valohai Machine Learning Operations (MLOps) Introduction
11.16.4 Valohai Revenue in Machine Learning Operations (MLOps) Business (2019-2024)
11.16.5 Valohai Recent Developments
12 Analyst's Viewpoints/Conclusions
13 Appendix
13.1 Research Methodology
13.1.1 Methodology/Research Approach
13.1.2 Data Source
13.2 Disclaimer
13.3 Author Details
IBM
DataRobot
SAS
Microsoft
Amazon
Google
Dataiku
Databricks
HPE
Lguazio
ClearML
Modzy
Comet
Cloudera
Paperpace
Valohai
听
听
*If Applicable.
