Compare Control-M and Snowflake 
At a Glance
Market Segments
Enterprise (61.5% of reviews)
Enterprise (44.4% of reviews)
Entry-Level Pricing
Starting at $29,000.00 500 Executions Per Month
$2 Compute/Hour
Control-M
Star Rating
(157)4.3 out of 5
Market Segments
Enterprise (61.5% of reviews)
Pros & Cons
Entry-Level Pricing
Starting at $29,000.00 500 Executions Per Month
Learn more about Control-MSnowflake
Star Rating
(695)4.6 out of 5
Market Segments
Enterprise (44.4% of reviews)
Pros & Cons
Entry-Level Pricing
$2 Compute/Hour
Free Trial is available
Browse all 4 pricing plansSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- G2 reviewers report that Snowflake excels in user experience, particularly highlighting its intuitive interface and the ability to separate storage from compute. This feature allows for efficient scaling and fast query performance, making it a favorite among data engineers for tasks like ETL and machine learning.
- Users say Control-M stands out for its powerful automation and centralized workflow management. Reviewers appreciate how it simplifies job scheduling and monitoring across multiple systems, which enhances operational efficiency and reliability.
- According to verified reviews, Snowflake's ease of setup is a significant advantage, with many users praising its straightforward onboarding process. This contrasts with Control-M, where some users have noted that adapting to its features can be more complex, especially for new users.
- Reviewers mention that Snowflake's recent updates, including ML/AI features, keep it competitive in the market, particularly for users looking to integrate with BI tools like Power BI. In comparison, Control-M is recognized for its robust scheduling capabilities but lacks the same level of innovation in data processing features.
- Users highlight that Snowflake's strong performance in data distribution and real-time data collection makes it a preferred choice for organizations dealing with large datasets. Control-M, while effective in workload processing, does not match Snowflake's capabilities in these areas.
- G2 reviewers note that both products have solid support, but Snowflake edges out with slightly higher satisfaction ratings. Users appreciate the responsive support team and the wealth of resources available for troubleshooting, which enhances their overall experience with the platform.
Pricing
Entry-Level Pricing
Control-M
Starter Pack (SaaS)
Starting at $29,000.00
500 Executions Per Month
Full-featured Control-M SaaS orchestration — right-sized for growing teams and hybrid cloud apps.
- Visual Workflow Designer
- Cloud native & hybrid app integration
- API jobs, event triggers, file transfer
Snowflake
Standard
$2
Compute/Hour
Compute usage is billed on a per-second basis, with a minimum of 60 seconds. You can secure price discounts with pre-purchased Snowflake capacity options.
- Complete SQL Data Warehouse
- Secure Data Sharing across regions / clouds
- Premier Support 24 x 365
Free Trial
Control-M
No trial information availableSnowflake
Free Trial is available
Ratings
Meets Requirements
9.0
95
9.1
528
Ease of Use
8.7
97
9.0
564
Ease of Setup
8.2
64
8.9
349
Ease of Admin
8.6
43
8.7
213
Quality of Support
8.5
91
8.7
484
Has the product been a good partner in doing business?
8.9
44
9.0
215
Product Direction (% positive)
8.6
93
9.2
497
Features by Category
Automation
9.1
54
Not enough data
8.8
51
Not enough data
8.1
28
Not enough data
Administration
7.9
50
Not enough data
9.0
50
Not enough data
8.4
43
Not enough data
8.3
26
Not enough data
8.5
31
Not enough data
8.5
25
Not enough data
Functionality
9.4
63
Not enough data
8.4
44
Not enough data
8.7
33
Not enough data
Agentic AI - Workload Automation
8.5
11
Not enough data
8.8
10
Not enough data
8.7
14
Not enough data
7.6
9
Not enough data
7.2
9
Not enough data
7.2
10
Not enough data
7.6
9
Not enough data
Deployment
Not enough data
9.2
12
Not enough data
8.9
12
Not enough data
9.0
12
Not enough data
9.3
12
Not enough data
9.3
12
Deployment
Not enough data
9.3
10
Not enough data
9.5
10
Not enough data
9.5
10
Not enough data
9.5
10
Not enough data
9.3
10
Management
Not enough data
9.2
12
Not enough data
9.0
12
Not enough data
9.2
12
Not enough data
9.0
12
Operations
Not enough data
8.8
10
Not enough data
8.8
10
Not enough data
9.5
10
Management
Not enough data
9.2
10
Not enough data
9.3
9
Not enough data
9.0
10
Generative AI
Not enough data
8.7
10
Not enough data
8.3
10
Functionality
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Management
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Agentic AI - Continuous Delivery
Not enough data
Not enough data
Not enough data
Not enough data
Feature Not Available
Not enough data
Not enough data
Not enough data
Feature Not Available
Not enough data
System
Not enough data
9.2
28
Model Development
Not enough data
9.1
30
Not enough data
8.5
28
Not enough data
8.2
28
Not enough data
8.7
29
Model Development
Not enough data
8.7
27
Machine/Deep Learning Services
Not enough data
8.5
28
Not enough data
8.5
28
Not enough data
8.3
28
Not enough data
8.3
27
Machine/Deep Learning Services
Not enough data
8.5
27
Not enough data
8.5
24
Deployment
Not enough data
9.1
30
Not enough data
9.0
27
Not enough data
9.2
29
Generative AI
Not enough data
8.5
26
Not enough data
8.3
25
Not enough data
8.5
25
Agentic AI - Data Science and Machine Learning Platforms
Not enough data
8.2
13
Not enough data
8.2
13
Not enough data
8.3
13
Not enough data
8.5
13
Not enough data
8.2
13
Not enough data
8.3
14
Not enough data
8.2
13
Data Management
Not enough data
9.0
192
|
Verified
Not enough data
8.9
173
|
Verified
Not enough data
9.0
180
|
Verified
Not enough data
8.3
177
|
Verified
Not enough data
8.2
155
|
Verified
Not enough data
8.7
158
|
Verified
Integration
Not enough data
8.3
148
|
Verified
Not enough data
8.9
181
|
Verified
Not enough data
8.9
163
|
Verified
Deployment
Not enough data
7.7
142
|
Verified
Not enough data
9.3
188
|
Verified
Performance
Not enough data
9.3
192
|
Verified
Security
Not enough data
8.9
176
|
Verified
Not enough data
9.1
184
|
Verified
Generative AI
Not enough data
7.9
81
Not enough data
8.1
81
Management
Not enough data
8.9
84
Not enough data
9.1
84
Not enough data
9.4
91
Not enough data
9.0
88
Not enough data
9.1
89
Maintenance
Not enough data
9.3
87
Not enough data
9.0
85
Not enough data
9.3
89
Security
Not enough data
9.2
86
Not enough data
9.3
89
Functionality
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Management
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Agentic AI - Continuous Integration
Not enough data
Not enough data
Not enough data
Not enough data
Feature Not Available
Not enough data
Not enough data
Not enough data
Feature Not Available
Not enough data
Development
Not enough data
Not enough data
Feature Not Available
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Feature Not Available
Not enough data
Management
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Security
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Integration Options
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Deployment
Not enough data
Not enough data
Not enough data
Not enough data
Storage
Not enough data
9.2
44
Not enough data
9.2
44
Availability
Not enough data
9.1
39
Not enough data
9.2
37
Not enough data
9.2
41
Performance
Not enough data
9.2
44
Security
Not enough data
9.1
44
Not enough data
9.2
45
Not enough data
8.9
38
Not enough data
9.2
38
Support
Not enough data
9.2
36
Not enough data
9.1
35
Centralized computation
Not enough data
9.3
25
Localized computation
Not enough data
9.0
24
Automation Support - Runbook Automation
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Error Management - Runbook Automation
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Customization - Runbook Automation
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Compliance and Reporting - Runbook Automation
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Performance - Runbook Automation
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Agentic AI - Runbook Automation
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Feature Not Available
Not enough data
Not enough data
Not enough data
Feature Not Available
Not enough data
Not enough data
Not enough data
Database
8.6
6
8.9
98
7.8
6
9.3
101
8.3
6
9.3
95
Integrations
Not enough data
8.6
76
Not enough data
8.7
81
Platform
8.0
5
9.1
92
7.3
5
9.0
97
Not enough data
8.7
81
Processing
Not enough data
9.3
97
9.2
6
9.1
95
Data Transformation
Not enough data
9.2
87
Not enough data
9.4
88
Connectivity
Not enough data
8.5
78
Not enough data
8.7
79
Not enough data
9.1
81
Not enough data
9.1
81
Operations
Not enough data
8.6
84
Not enough data
9.2
79
Not enough data
8.9
76
Not enough data
8.8
80
Not enough data
8.7
78
Building Reports
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Platform
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Categories
Categories
Shared Categories
Control-M and Snowflake are categorized as Big Data Processing and Distribution and Big Data Integration Platforms
Unique Categories
Control-M is categorized as Workload Automation, Runbook Automation, iPaaS, Build Automation, Continuous Integration, and Continuous Delivery
Snowflake is categorized as Data Clean Room, Columnar Databases, MLOps Platforms, Big Data Analytics, Database Management Systems (DBMS), Data Warehouse, and Data Science and Machine Learning Platforms
Reviews
Reviewers' Company Size
Control-M
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Snowflake
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Small-Business
(50 or fewer emp.)
Mid-Market
(51-1000 emp.)
Enterprise
(> 1000 emp.)
Reviewers' Industry
Information Technology and Services
24.2%
Banking
8.3%
Financial Services
8.3%
Telecommunications
7.5%
Retail
5.8%
Other
45.8%
Information Technology and Services
15.0%
Computer Software
13.4%
Financial Services
10.2%
Marketing and Advertising
4.7%
Hospital & Health Care
3.6%
Other
53.1%
Alternatives
Discussions
Is Control-M an ETL tool?
2 Comments
LV
Yes. Control-M is used for scheduling and monitoring the jobs in ETL.Read more
What does control-M software do?
1 Comment
SS
I used it in banking requirrd to automate job and scheduler.Read more
What is workflow in control-M?
1 Comment
LV
Control-M Workflow Insights provides valuable dashboards that give users in-depth observability to continuously monitor and improve performance of the...Read more
What's the best way to manage change data capture in Snowflake?
4 Comments
VT
Please go through this link: https://docs.snowflake.com/en/user-guide/streams
You might get a pertinent response from it.
Please click on this link...Read more
which is best snowflake or My sql
2 Comments
LH
Depends on your needs. MySQL is open source/free. It or Postgres (another open source db) is good for pretty much any normal need. You can install on...Read more
Snowflake - how to connect to Snowflake using NodeJS
2 Comments
DW
Does this help? https://www.ameexusa.com/blogs/connecting-node-js-snowflakeRead more
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