Compare Apache Pig and dbt 
Featured Products
At a Glance
Market Segments
Enterprise (65.0% of reviews)
Mid-Market (57.7% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
Apache Pig
Star Rating
(21)3.9 out of 5
Market Segments
Enterprise (65.0% of reviews)
Pros & Cons
Not enough data
Entry-Level Pricing
No pricing available
Learn more about Apache Pigdbt
Star Rating
(199)4.7 out of 5
Market Segments
Mid-Market (57.7% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about dbtSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- G2 reviewers report that dbt excels in user satisfaction, boasting a significantly higher overall rating compared to Apache Pig. Users appreciate dbt's intuitive setup and daily usability, with one reviewer highlighting its ease of integration and the structured approach it brings to data work.
- According to verified reviews, Apache Pig is praised for its powerful query language, Pig Latin, which allows users to create data pipelines efficiently. However, some users feel it may require more technical knowledge compared to dbt, which is designed to be user-friendly for a broader audience.
- Users say that dbt's implementation process is smooth and quick, with no delays reported during setup. In contrast, while Apache Pig is noted for its automation of MapReduce tasks, some users mention that it can be challenging to configure for specific workflows.
- Reviewers mention that dbt provides excellent support, with a high quality of assistance reported by users. On the other hand, Apache Pig's support quality is seen as a weak point, with users expressing concerns about responsiveness and helpfulness.
- G2 reviewers highlight that dbt's ability to automate data model creation instills confidence in the accuracy of KPIs, a feature that many users find invaluable. While Apache Pig offers robust capabilities for complex data processing, it lacks the same level of trust and reliability in data transformation as reported by dbt users.
- According to recent user feedback, Apache Pig is favored for its Hadoop integration capabilities, making it a strong choice for enterprises already invested in that ecosystem. However, dbt's focus on mid-market users and its seamless integration with tools like BigQuery make it a compelling option for teams looking for a more modern data transformation solution.
Pricing
Entry-Level Pricing
Apache Pig
No pricing availabledbt
No pricing availableFree Trial
Apache Pig
No trial information availabledbt
Free Trial is available
Ratings
Meets Requirements
7.7
17
9.2
147
Ease of Use
7.6
18
9.0
149
Ease of Setup
7.7
5
8.6
88
Ease of Admin
9.0
5
8.5
59
Quality of Support
5.7
17
8.9
118
Has the product been a good partner in doing business?
Not enough data
8.6
53
Product Direction (% positive)
4.2
18
9.6
134
Features by Category
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
Not enough data
Not enough data
Self Service
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
Advanced Analytics
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
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
Data Source Access
Not enough data
8.8
47
Not enough data
9.2
50
Not enough data
8.6
41
Data Interaction
Not enough data
8.3
40
Not enough data
8.5
44
Not enough data
9.0
50
Not enough data
9.1
48
Not enough data
9.1
42
Not enough data
9.4
48
Not enough data
8.7
47
Not enough data
8.7
45
Data Exporting
Not enough data
8.5
41
Not enough data
8.7
44
Not enough data
9.1
45
Generative AI
Not enough data
6.5
27
Management
Not enough data
Feature Not Available
Not enough data
8.2
37
Functionality
Not enough data
Feature Not Available
Not enough data
9.3
45
Not enough data
Feature Not Available
Not enough data
9.5
40
Not enough data
9.2
37
Data Management
Not enough data
9.2
51
Not enough data
9.1
52
Not enough data
9.1
49
Not enough data
9.3
49
Agentic AI - DataOps Platforms
Not enough data
7.5
8
Not enough data
7.4
7
Not enough data
8.1
9
Not enough data
8.1
9
Not enough data
8.3
8
Analytics
Not enough data
8.8
48
Not enough data
7.3
34
Monitoring and Management
Not enough data
8.7
43
Not enough data
8.9
51
Cloud Deployment
Not enough data
8.7
37
Not enough data
8.8
29
Generative AI
Not enough data
5.7
12
Not enough data
6.0
12
Automation
Not enough data
8.8
34
Not enough data
8.3
32
Not enough data
8.6
35
Not enough data
Feature Not Available
Functionality
Not enough data
8.6
34
Not enough data
8.6
34
Not enough data
8.4
34
Administration
Not enough data
8.4
37
Not enough data
8.9
34
Not enough data
9.1
35
Agentic AI - Data Warehouse Automation
Not enough data
Not enough data
Deployment & Integration - Semantic Layer Tools
Not enough data
Not enough data
Not enough data
Not enough data
Data Connectivity & Federation - Semantic Layer Tools
Not enough data
Not enough data
Not enough data
Not enough data
Data Modeling & Metrics - Semantic Layer Tools
Not enough data
Not enough data
Not enough data
Not enough data
Performance Optimization - Semantic Layer Tools
Not enough data
Not enough data
Not enough data
Not enough data
Governance - Semantic Layer Tools
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Advanced Intelligence - Semantic Layer Tools
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Agentic AI Enablement - Semantic Layer Tools
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Data Transformation
Not enough data
8.5
32
Not enough data
9.4
39
Connectivity
9.0
5
|
Verified
8.4
27
Not enough data
8.6
28
Not enough data
8.5
34
Feature Not Available
8.9
31
Operations
Not enough data
Feature Not Available
Not enough data
9.3
38
Feature Not Available
8.6
30
Feature Not Available
8.7
30
Feature Not Available
8.6
30
Functionality
Not enough data
8.7
39
Not enough data
8.3
36
Not enough data
8.7
40
Not enough data
8.2
38
Not enough data
8.4
38
Management
Not enough data
8.5
40
Not enough data
9.3
42
Not enough data
8.8
36
Not enough data
8.1
39
Not enough data
8.3
41
Generative AI
Not enough data
6.2
19
Not enough data
6.6
19
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 Pig and dbt are categorized as Big Data Analytics
Unique Categories
Apache Pig has no unique categories
dbt is categorized as Big Data Integration Platforms, Data Preparation, Data Quality, ETL Tools, Data Warehouse Automation, DataOps Platforms, and Semantic Layer Tools
Reviews
Reviewers' Company Size
Apache Pig
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
dbt
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
Internet
25.0%
Computer Software
25.0%
Marketing and Advertising
15.0%
Information Technology and Services
15.0%
Telecommunications
5.0%
Other
15.0%
Information Technology and Services
19.4%
Computer Software
16.3%
Financial Services
10.2%
Retail
5.1%
Marketing and Advertising
4.6%
Other
44.4%
Alternatives
Discussions
Apache Pig has no discussions with answers
What is DBT data Modelling?
2 Comments
TH
dbt data modeling is not a thing. Dbt is a transformation tool that makes it easier to implement data modeling techniques like snowflake, data vault etc. Read more
What is DBT tool used for?
2 Comments
WW
Data transformations. The 'T' in ELT/ELT. It lets you version-control and easily modify all your data transformations between (say) your source tables from...Read more
What is DBT technology?
1 Comment
TH
dbt is a data transformation tool that helps organize & run SQL files. The SQL files are only SELECT statements while dbt takes care of the boilerplate...Read more
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