Deequ vs Elementary
Verdict: Deequ scores 8.4/10 against 8.4/10 for Elementary on our data score for data quality tools.
Both have a free plan.
Elementary leads on 1 check and Deequ on 0; 4 are even, out of 5 checks (yes/no, price and seats) where we have data for both.
Choose Deequ for spark and Scala/Python engineers validating large datasets in batch pipelines. Choose Elementary for analytics engineering teams that build with dbt.
Scoreboard: 5 checks
| Check | Deequ | Elementary |
|---|---|---|
| Free plan | Even | Even |
| Free trial | Leads | |
| Smaller seat minimum | Even | Even |
| Custom rule checks | Even | Even |
| Open source | Even | Even |
| Total | 0 | 1 |
At a glance
| Deequ | Elementary | |
|---|---|---|
| Score | 8.4/10 (#3) | 8.4/10 (#4) |
| Best for | Spark and Scala/Python engineers validating large datasets in batch pipelines | Analytics engineering teams that build with dbt |
| Free plan | Yes | Yes |
| Paid from (annual) | See vendor | See vendor |
| Paid from (monthly) | — | — |
| Free trial | — | 30-day free trial of Elementary Cloud |
| Minimum seats | 1 | 1 |
| Platforms | Self-hosted (Apache Spark library) | Cloud (SaaS), Self-hosted (OSS) |
Features
| Tool | Score | Data profiling | Custom rule checks | ML anomaly detection | Data cleansing / correction | Open source |
|---|---|---|---|---|---|---|
| Deequ | 8.4/10 | Yes | Yes | Not confirmed | Not confirmed | Yes |
| Elementary | 8.4/10 | Not confirmed | Yes | Yes | Not confirmed | Yes |
- Only Deequ confirms: Data profiling.
- Only Elementary confirms: ML anomaly detection.
Pros and cons
Deequ
Pros- Free and open source (Apache-2.0)
- Scales with Apache Spark for very large datasets
- Automatic constraint suggestion and column profiling
- Supports AWS Data Quality Definition Language (DQDL) rules
- Library only: no UI, scheduling or alerting built in
- Requires Spark; releases are tied to specific Spark versions
- Recent versions (2.1.0+) require Java 11
Elementary
Pros- Open-source dbt package and CLI (Apache-2.0) can be self-hosted at no cost
- Tests are configured in the dbt project as code, alongside existing dbt tests
- 30-day cloud trial with no limits on seats, environments or monitored tables
- Elementary states it is SOC 2 Type II certified and the cloud reads metadata only
- Mainly useful for teams already using dbt
- Cloud prices are not published ('Talk to sales')
- Pricing page has inconsistencies (trial references an 'Essentials' plan that is not listed)
- AI agents are billed separately with credits
Frequently asked questions
How do Deequ and Elementary compare on features and price?
Elementary leads on 1 check and Deequ on 0; 4 are even, out of 5 checks (yes/no, price and seats) where we have data for both.
Is Deequ better than Elementary?
Deequ scores 8.4/10 against 8.4/10 for Elementary on our data score for data quality tools. Deequ is best for spark and Scala/Python engineers validating large datasets in batch pipelines; Elementary is best for analytics engineering teams that build with dbt.
Which is cheaper, Deequ or Elementary?
Check each vendor's pricing page; one of them does not publish an entry price.
Do Deequ and Elementary have free plans?
Deequ: yes. Elementary: yes.
See the full Data Quality Tools ranking for other options.