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Compare ClickHouse and Spark SQL 
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At a Glance
Market Segments
Small-Business (47.4% of reviews)
Enterprise (53.3% of reviews)
Entry-Level Pricing
Starting at $1.00 Per Month
No pricing available
ClickHouse
Star Rating
(20)4.4 out of 5
Market Segments
Small-Business (47.4% of reviews)
Entry-Level Pricing
Starting at $1.00 Per Month
Learn more about ClickHouseSpark 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 Spark SQL excels in its query language capabilities, scoring 9.3, which allows for complex data manipulations and integrations with existing Spark applications. In contrast, ClickHouse's query language received a score of 9.3 as well, but users mention that it is more tailored for analytical queries, making it less versatile for general-purpose data processing.
- Reviewers mention that Spark SQL has a strong data modeling feature with a score of 9.4, which is beneficial for users needing to create complex data structures. ClickHouse, while scoring similarly in data model at 9.0, is noted for its simplicity in handling large datasets, which some users find advantageous for straightforward analytical tasks.
- G2 users highlight that Spark SQL's ease of use is rated at 9.0, making it user-friendly for those familiar with SQL and Spark. Conversely, ClickHouse, with a score of 8.5, is reported to have a steeper learning curve, particularly for users not accustomed to its specific optimizations and configurations.
- Users on G2 report that Spark SQL's performance analysis capabilities are top-notch, achieving a perfect score of 10.0, which helps users optimize their queries effectively. ClickHouse also performs well but is noted for its query latency advantages, particularly in high-volume environments, which some users find critical for real-time analytics.
- Reviewers mention that Spark SQL's data replication feature scores 7.9, which some users find lacking in comparison to ClickHouse's score of 8.0. Users appreciate ClickHouse's more robust replication mechanisms, which are essential for maintaining data integrity across distributed systems.
- Users say that Spark SQL's backup and recovery options score 7.8, which some find less comprehensive than ClickHouse's offerings. ClickHouse's higher score in this area indicates a more reliable system for users concerned about data loss and recovery processes.
Pricing
Entry-Level Pricing
ClickHouse
ClickHouse Pricing
Starting at $1.00
Per Month
Options for every user, organization, and use case.
- Up to 1 TB storage
- 16 GiB total memory
- Burstable CPU
Spark SQL
No pricing availableFree Trial
ClickHouse
No trial information availableSpark SQL
No trial information availableRatings
Meets Requirements
8.9
11
8.8
32
Ease of Use
8.6
11
9.0
35
Ease of Setup
9.0
7
8.7
14
Ease of Admin
7.0
5
8.2
13
Quality of Support
8.7
9
8.4
32
Has the product been a good partner in doing business?
Not enough data
8.6
14
Product Direction (% positive)
10.0
10
10.0
29
Features by Category
Management
9.4
6
Not enough data
7.9
7
Not enough data
9.3
7
Not enough data
9.4
6
Not enough data
10.0
5
Not enough data
Maintenance
8.8
7
Not enough data
7.8
6
Not enough data
Not enough data
Not enough data
Security
Not enough data
Not enough data
Not enough data
Not enough data
Management
Not enough data
8.7
26
9.3
5
8.5
26
Feature Not Available
8.3
23
Not enough data
8.3
26
Support
Not enough data
8.0
23
Not enough data
8.1
27
Not enough data
8.2
26
Not enough data
8.8
24
Security
Feature Not Available
8.7
24
Not enough data
8.3
23
Not enough data
8.4
22
Not enough data
8.5
24
Performance
Not enough data
8.7
25
Not enough data
8.5
25
Not enough data
8.6
25
Not enough data
7.9
23
Not enough data
8.6
25
Database Features
9.0
5
8.3
26
9.3
5
8.7
26
9.0
5
8.7
27
9.0
5
8.9
27
Not enough data
8.5
27
Not enough data
8.5
26
8.7
5
8.3
27
Storage
9.2
6
Not enough data
9.0
7
Not enough data
Availability
Feature Not Available
Not enough data
7.8
6
Not enough data
8.3
6
Not enough data
Performance
8.1
6
Not enough data
Security
9.0
5
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
8.3
5
Not enough data
Support
Not enough data
Not enough data
Not enough data
Not enough data
Query latency
Not enough data
Not enough data
Not enough data
Not enough data
Data latency
Not enough data
Not enough data
Not enough data
Not enough data
Connectors
Not enough data
Not enough data
Not enough data
Not enough data
Scale
Not enough data
Not enough data
Not enough data
Not enough data
Architecture
Not enough data
Not enough data
Not enough data
Not enough data
Categories
Categories
Shared Categories
ClickHouse and Spark SQL are categorized as Relational Databases
Unique Categories
ClickHouse is categorized as Real-time Analytic Database, Database Management Systems (DBMS), and Columnar Databases
Spark SQL has no unique categories
Reviews
Reviewers' Company Size
ClickHouse
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
31.6%
Computer Software
21.1%
Wholesale
5.3%
Telecommunications
5.3%
Marketing and Advertising
5.3%
Other
31.6%
Information Technology and Services
31.1%
Computer Software
13.3%
Retail
6.7%
Financial Services
6.7%
Telecommunications
4.4%
Other
37.8%
Discussions
ClickHouse has no discussions with answers
What type of SQL does Spark use?
2 Comments
PS
Spark SqlRead 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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