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Compare Microsoft SQL Server and Spark SQL 
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At a Glance
Market Segments
Enterprise (45.6% of reviews)
Enterprise (53.3% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
Microsoft SQL Server
Star Rating
(2,252)4.4 out of 5
Market Segments
Enterprise (45.6% of reviews)
Entry-Level Pricing
No pricing available
Learn more about Microsoft SQL ServerSpark SQL
Star Rating
(45)4.5 out of 5
Market Segments
Enterprise (53.3% of reviews)
Entry-Level Pricing
No pricing available
Learn more about Spark SQLSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Microsoft SQL Server excels in its Query Language with a score of 9.2, making it a preferred choice for complex queries, while Spark SQL, with a score of 8.5, is noted for its flexibility but may not match the depth of SQL Server's capabilities.
- Reviewers mention that Microsoft SQL Server's Data Migration feature scores a high 9.0, indicating a smooth transition process, whereas Spark SQL's migration capabilities are less emphasized, leading to potential challenges for users migrating from traditional databases.
- G2 users highlight the superior Backup and Recovery options in Microsoft SQL Server, also rated at 9.0, which provides peace of mind for data integrity, while Spark SQL's backup features are less robust, scoring lower in user satisfaction.
- Users on G2 appreciate Microsoft SQL Server's strong User Access Control with a score of 9.1, which enhances security and management, while Spark SQL's access control features, scoring 8.3, are seen as less comprehensive, potentially leading to security concerns.
- Reviewers say that Microsoft SQL Server's Performance and Reliability is rated at 9.2, making it a reliable choice for enterprise-level applications, while Spark SQL, with a score of 8.6, is recognized for its speed but may not always guarantee the same level of reliability.
- Users report that Microsoft SQL Server's Data Types support, scoring 9.0, is extensive and well-documented, which is crucial for developers, whereas Spark SQL, with a score of 8.1, has limitations in data type support that can hinder certain applications.
Pricing
Entry-Level Pricing
Microsoft SQL Server
No pricing availableSpark SQL
No pricing availableFree Trial
Microsoft SQL Server
No trial information availableSpark SQL
No trial information availableRatings
Meets Requirements
9.0
1,847
8.8
32
Ease of Use
8.6
1,863
9.0
35
Ease of Setup
8.1
984
8.7
14
Ease of Admin
8.3
945
8.2
13
Quality of Support
8.3
1,641
8.4
32
Has the product been a good partner in doing business?
8.4
895
8.6
14
Product Direction (% positive)
8.4
1,818
10.0
29
Features by Category
Management
8.9
150
Not enough data
8.9
150
Not enough data
9.2
155
Not enough data
8.9
150
Not enough data
8.9
152
Not enough data
Maintenance
8.9
150
Not enough data
9.0
155
Not enough data
9.0
151
Not enough data
Security
8.9
149
Not enough data
9.1
151
Not enough data
Management
9.1
147
8.7
26
9.2
148
8.5
26
8.8
134
8.3
23
8.9
140
8.3
26
Support
8.6
143
8.0
23
9.1
147
8.1
27
8.7
142
8.2
26
8.5
146
8.8
24
Security
8.9
146
8.7
24
9.1
146
8.3
23
8.9
143
8.4
22
9.0
146
8.5
24
Performance
8.8
142
8.7
25
8.9
139
8.5
25
8.8
145
8.6
25
8.7
143
7.9
23
8.9
144
8.6
25
Database Features
8.9
1282
8.3
26
9.0
1287
8.7
26
8.9
1294
8.7
27
8.7
1261
8.9
27
8.8
1263
8.5
27
8.8
1269
8.5
26
9.1
1289
8.3
27
Database
8.6
55
Not enough data
8.8
56
Not enough data
8.4
53
Not enough data
Integrations
7.8
44
Not enough data
8.3
44
Not enough data
Platform
8.3
49
Not enough data
8.6
52
Not enough data
8.3
44
Not enough data
Processing
8.6
51
Not enough data
8.5
54
Not enough data
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
Microsoft SQL Server and Spark SQL are categorized as Relational Databases
Unique Categories
Microsoft SQL Server is categorized as Database Management Systems (DBMS), Big Data Processing and Distribution, and On-Premise Data Integration
Spark SQL has no unique categories
Reviews
Reviewers' Company Size
Microsoft SQL Server
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Spark SQL
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%
Computer Software
13.7%
Hospital & Health Care
5.4%
Financial Services
4.3%
Higher Education
2.9%
Other
49.6%
Information Technology and Services
31.1%
Computer Software
13.3%
Retail
6.7%
Financial Services
6.7%
Telecommunications
4.4%
Other
37.8%
Alternatives
Discussions
What is the best way to save your queries?
4 Comments
CA
I recommend that you use the saved querys in plain text or .sql or txt format you can use the same sql server query creator or a notepad +++ tool, they are...Read more
How could I make much easier the experience with the order of my database?
4 Comments
AF
You can create different tables with your employee information eg employee table, employee roles etc. Then you can create a single view that will pull data...Read more
How can I work on the same query if the connection is lost (timeout) and then I reconnect?
4 Comments
JE
When this happens to me in SQL Server Management Studio, I just have to type USE {your database name here} and then select only that statement and execute...Read more
What is the difference between SQL and Spark SQL?
1 Comment
NK
Well it's very simple spark sql is used for big data processing, it makes querying the loads of data simple and faster.
Whereas sql isn't suitable for...Read more
What is the functionality of Spark SQL?
1 Comment
NK
Spark sql works with any kind of relational databases that works with sql like Mysql, oracle, mariadb, postgresqlRead more
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