Compare Apache Parquet and Druid 
At a Glance
Market Segments
Mid-Market (50.0% of reviews)
Enterprise (57.1% of reviews)
Pros & Cons
Not enough data
Not enough data
Entry-Level Pricing
No pricing available
No pricing available
Apache Parquet
Star Rating
(27)4.3 out of 5
Market Segments
Mid-Market (50.0% of reviews)
Pros & Cons
Not enough data
Entry-Level Pricing
No pricing available
Learn more about Apache ParquetDruid
Star Rating
(31)4.3 out of 5
Market Segments
Enterprise (57.1% of reviews)
Pros & Cons
Not enough data
Entry-Level Pricing
No pricing available
Learn more about DruidApache Parquet vs Druid
When assessing the two solutions, reviewers found Druid easier to use and do business with overall. However, reviewers preferred the ease of set up with Apache Parquet, along with administration.
- Reviewers felt that Apache Parquet meets the needs of their business better than Druid.
- When comparing quality of ongoing product support, reviewers felt that Apache Parquet is the preferred option.
- For feature updates and roadmaps, our reviewers preferred the direction of Apache Parquet over Druid.
Pricing
Entry-Level Pricing
Apache Parquet
No pricing availableDruid
No pricing availableFree Trial
Apache Parquet
No trial information availableDruid
Free Trial is available
Ratings
Meets Requirements
8.5
21
8.4
20
Ease of Use
7.7
22
8.0
20
Ease of Setup
7.2
9
6.4
7
Ease of Admin
7.6
9
6.4
7
Quality of Support
8.1
19
7.9
18
Has the product been a good partner in doing business?
7.5
8
7.7
5
Product Direction (% positive)
8.6
25
7.3
17
Features by Category
Data Management
Not enough data
8.3
5
Not enough data
8.0
5
Not enough data
8.7
5
Not enough data
8.7
5
Not enough data
Not enough data
Not enough data
8.0
5
Integration
Not enough data
Not enough data
Not enough data
7.0
5
Not enough data
Not enough data
Deployment
Not enough data
Not enough data
Not enough data
8.3
5
Performance
Not enough data
8.3
5
Security
Not enough data
Not enough data
Not enough data
Not enough data
Generative AI
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
Not enough data
Not enough data
Support
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
Not enough data
Not enough data
Performance
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
Database Features
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
Storage
9.0
13
8.8
10
8.8
12
7.8
10
Availability
7.4
14
8.7
9
8.2
12
7.6
9
8.8
12
8.3
10
Performance
8.6
12
8.9
9
Security
9.0
12
8.1
8
7.9
12
9.3
7
7.9
12
8.7
10
8.6
12
8.5
8
Support
8.9
12
8.8
10
8.2
12
9.2
11
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
Database
Not enough data
8.5
10
Not enough data
8.7
10
Not enough data
8.8
8
Integrations
Not enough data
8.8
8
Not enough data
8.1
9
Platform
Not enough data
8.5
9
Not enough data
8.7
9
Not enough data
8.1
9
Processing
Not enough data
8.6
7
Not enough data
8.7
9
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
Apache Parquet and Druid are categorized as Columnar Databases
Unique Categories
Apache Parquet has no unique categories
Druid is categorized as Real-time Analytic Database, Time Series Databases, Relational Databases, Data Warehouse, and Big Data Processing and Distribution
Reviews
Reviewers' Company Size
Apache Parquet
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Druid
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
Computer Software
38.5%
Information Technology and Services
19.2%
Financial Services
7.7%
Education Management
7.7%
Hospital & Health Care
3.8%
Other
23.1%
Computer Software
28.6%
Telecommunications
10.7%
Leisure, Travel & Tourism
10.7%
Retail
7.1%
Information Technology and Services
7.1%
Other
35.7%
Alternatives
Discussions
Apache Parquet has no discussions with answers
Is it good to use Druid (for a small dataset) as an in-memory database ?
1 Comment
DG
Yes it is good for medium size data sets to big scale datasetsRead more
Druid has no more discussions with answers
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