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Compare Apache Ignite and Druid 
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At a Glance
Market Segments
Mid-Market (35.3% 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 Ignite
Star Rating
(17)3.9 out of 5
Market Segments
Mid-Market (35.3% of reviews)
Pros & Cons
Not enough data
Entry-Level Pricing
No pricing available
Learn more about Apache IgniteDruid
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 Ignite excels in real-time data collection with a score of 8.5, making it a strong choice for applications requiring immediate data processing. In contrast, Druid, while also capable, does not match this level of performance in real-time capabilities.
- Reviewers mention that Apache Ignite's data management features, particularly its data model and data types, score highly at 8.8 and 7.8 respectively, indicating a robust framework for handling diverse data structures. Druid, however, has a lower score in data types, which may limit its flexibility in certain use cases.
- G2 users highlight that Druid shines in data lake integration with a score of 8.8, making it particularly suitable for analytics on large datasets. Users say that this feature is crucial for organizations looking to leverage big data effectively, whereas Apache Ignite does not emphasize this capability as strongly.
- Reviewers mention that Apache Ignite's auto sharding feature scores an impressive 8.7, which enhances its scalability and performance under heavy loads. In comparison, Druid's performance in this area is not as robust, potentially leading to challenges in scaling during peak usage times.
- Users on G2 report that Druid's BI tool integration scores a modest 7.0, indicating some limitations in connecting with business intelligence platforms. In contrast, Apache Ignite's integration capabilities are generally viewed more favorably, allowing for smoother workflows and data analysis.
- Reviewers mention that while both products offer strong security features, Druid's role-based authorization and authentication scores of 8.1 and 9.3 respectively, are particularly praised, suggesting a more comprehensive approach to user access control compared to Apache Ignite.
Pricing
Entry-Level Pricing
Apache Ignite
No pricing availableDruid
No pricing availableFree Trial
Apache Ignite
No trial information availableDruid
Free Trial is available
Ratings
Meets Requirements
8.8
15
8.4
20
Ease of Use
7.4
16
8.0
20
Ease of Setup
7.8
6
6.4
7
Ease of Admin
7.5
6
6.4
7
Quality of Support
7.1
13
7.9
18
Has the product been a good partner in doing business?
6.1
6
7.7
5
Product Direction (% positive)
7.5
14
7.3
17
Features by Category
Functionality
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
Agentic AI - Database Monitoring
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
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
Not enough data
Not enough data
Maintenance
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
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
Data Management
Not enough data
Not enough data
Not enough data
Not enough data
Availability
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
Security
Feature Not Available
Not enough data
Not enough data
Not enough data
Feature Not Available
Not enough data
Not enough data
Not enough data
Support
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
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
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
Categories
Categories
Shared Categories
Apache Ignite and Druid are categorized as Relational Databases
Unique Categories
Apache Ignite is categorized as Key Value Databases, Database Management Systems (DBMS), and Database Monitoring
Druid is categorized as Real-time Analytic Database, Time Series Databases, Columnar Databases, Data Warehouse, and Big Data Processing and Distribution
Reviews
Reviewers' Company Size
Apache Ignite
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
Information Technology and Services
29.4%
Computer Software
17.6%
Financial Services
11.8%
Telecommunications
5.9%
Retail
5.9%
Other
29.4%
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 Ignite 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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