Datafold vs sieve
Comprehensive comparison for 2026: features, pricing, and expert recommendations
By Shyft Research TeamUpdated Feb 24, 2026
TL;DR
- Both tools is our recommended choice for most users
- Compare ratings, features, and pricing below
- See detailed pricing comparison below
- Choose Datafold for strong data lineage and quality control.
Datafold Rating
N/A
sieve Rating
N/A
Datafold Price
$49/mo
sieve Price
$29/mo
When comparing Datafold and Sieve, it's important to consider your specific data integration needs. Datafold focuses on automating data engineering tasks with AI, offering strong data lineage tracking and comprehensive quality checks. Sieve, on the other hand, combines AI with human review to solve data cleaning problems, providing flexibility through API or Excel access. Both tools are in the same tier, but they cater to different aspects of data integration.
Quick Verdict
Datafold excels in data lineage and quality checks. Sieve is better for collaborative data cleaning.
Choose Datafold
Datafold offers superior data lineage tracking and comprehensive quality checks. It is ideal for teams needing robust data governance.
Choose Datafold for strong data lineage and quality control.
OR
Choose sieve
Sieve combines AI with human review for effective data cleaning. It is accessible via API or Excel, making it versatile for various workflows.
Choose Sieve for collaborative data cleaning tasks.
Head-to-Head Comparison
Datafold
sieve
Category
data-integration
data-integration
Rating
No rating
No rating
Starting Price
$49/mo
$29/mo
Free Tier
What it Does
Automate data engineering tasks with AI
AI and human review for data cleaning
Frequently Asked Questions
In conclusion, Datafold is the better choice for teams prioritizing data lineage and quality checks. Sieve is ideal for those needing collaborative data cleaning solutions. Evaluate your specific requirements to make the best decision.
Our Expert Verdict
“Datafold excels in data lineage and quality checks. Sieve is better for collaborative data cleaning.”
Pros
- • Datafold: Established solution
- • sieve: Established solution
Recommendation: We recommend datafold for most use cases.
Verdict: Datafold vs sieve
Winner: datafold
Datafold excels in data lineage and quality checks. Sieve is better for collaborative data cleaning.
Common Questions: Datafold vs sieve
Both Datafold and sieve are strong data-integration tools. Datafold and sieve. The best choice depends on your team size, budget, and specific feature requirements. Both offer ways to try before you buy.