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Compare Apache Spark for Azure HDInsight and Druid 
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At a Glance
Market Segments
Mid-Market (63.6% 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 Spark for Azure HDInsight
Star Rating
(12)4.0 out of 5
Market Segments
Mid-Market (63.6% of reviews)
Pros & Cons
Not enough data
Entry-Level Pricing
No pricing available
Learn more about Apache Spark for Azure HDInsightDruid
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 DruidSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Apache Spark for Azure HDInsight excels in Hadoop Integration with a score of 9.4, making it a preferred choice for organizations already utilizing Hadoop ecosystems. In contrast, Druid, while still strong, scores lower at 8.8, indicating it may not integrate as seamlessly for Hadoop users.
- Reviewers mention that Apache Spark for Azure HDInsight offers superior Data Quality with a score of 8.7, which is crucial for businesses that rely on accurate data analytics. Druid, while competent, scores slightly lower at 8.5, suggesting it may not meet the same level of data integrity for all users.
- G2 users highlight that Apache Spark for Azure HDInsight provides better Ease of Use with a score of 8.5 compared to Druid's 8.0. This difference can significantly impact user adoption and productivity, especially for teams with varying technical expertise.
- Users on G2 report that Druid shines in Real-Time Data Collection, scoring 8.5, which is essential for businesses needing immediate insights. Apache Spark for Azure HDInsight, while still effective, scores higher at 8.9, indicating it may offer more robust capabilities in this area.
- Reviewers mention that Druid's Auto Sharding feature scores 8.7, which helps in managing large datasets efficiently. However, Apache Spark for Azure HDInsight's score of 8.3 suggests it may not be as effective in this aspect, potentially leading to challenges in scaling.
- Users say that Apache Spark for Azure HDInsight's Product Direction is rated positively at 8.8, indicating a strong commitment to future enhancements. In contrast, Druid's score of 7.3 suggests some users may have concerns about its long-term development and support.
Pricing
Entry-Level Pricing
Apache Spark for Azure HDInsight
No pricing availableDruid
No pricing availableFree Trial
Apache Spark for Azure HDInsight
No trial information availableDruid
Free Trial is available
Ratings
Meets Requirements
8.3
10
8.4
20
Ease of Use
8.5
10
8.0
20
Ease of Setup
Not enough data
6.4
7
Ease of Admin
Not enough data
6.4
7
Quality of Support
8.3
10
7.9
18
Has the product been a good partner in doing business?
Not enough data
7.7
5
Product Direction (% positive)
8.8
10
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
Not enough data
8.8
10
Not enough data
7.8
10
Availability
Not enough data
8.7
9
Not enough data
7.6
9
Not enough data
8.3
10
Performance
Not enough data
8.9
9
Security
Not enough data
8.1
8
Not enough data
9.3
7
Not enough data
8.7
10
Not enough data
8.5
8
Support
Not enough data
8.8
10
Not enough data
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
8.9
9
8.5
10
8.3
9
8.7
10
8.9
9
8.8
8
Integrations
9.4
9
8.8
8
8.9
9
8.1
9
Platform
8.7
9
8.5
9
8.3
9
8.7
9
8.9
9
8.1
9
Processing
8.7
9
8.6
7
8.1
9
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 Spark for Azure HDInsight and Druid are categorized as Big Data Processing and Distribution
Unique Categories
Apache Spark for Azure HDInsight has no unique categories
Druid is categorized as Real-time Analytic Database, Time Series Databases, Columnar Databases, Relational Databases, and Data Warehouse
Reviews
Reviewers' Company Size
Apache Spark for Azure HDInsight
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
Research
9.1%
Machinery
9.1%
Luxury Goods & Jewelry
9.1%
Information Technology and Services
9.1%
Higher Education
9.1%
Other
54.5%
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 Spark for Azure HDInsight 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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