Machine Learning · head to head
Dataiku vs PostgreSQL

Dataiku
Machine Learning
Browser-based platform where visual data preparation and written code share one pipeline
- From
- Free
- Rated
- -

PostgreSQL
Databases
The world's most advanced open source relational database
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Dataiku visual recipes are stored as Dataiku's own configuration and do not export as runnable SQL or Python, so a Flow with hundreds of visual steps has to be rebuilt from scratch if the organisation ever leaves, and that cost rises with every project added.; PostgreSQL requires manual scaling across multiple machines for very large deployments
- They diverge on capability: Dataiku covers Visual Flow, PostgreSQL covers ACID Compliance.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which Dataiku and PostgreSQL actually diverge.
| Attribute | Dataiku | PostgreSQL |
|---|---|---|
| Pricing model | freemium | Unknown |
| Platforms | Linux, Mac, Windows, Web | Linux, Windows, macOS, BSD, Unix |
| Category | Machine Learning | Databases |
| Founded | 2013 | 1996 |
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated).
What each one covers
Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.
Only in Dataiku
- Visual Flow
- Visual recipes
- Code recipes and notebooks
- Computation pushdown
- Automated machine learning
- Scenarios
- Node topology
- Governance features
Only in PostgreSQL
- ACID Compliance
- JSON/JSONB Support
- Full-text Search
- Extensibility
- Advanced Indexing
- Partitioning
- Replication
- pgAdmin
What people use each for
The jobs each tool is most often brought in to do.
Dataiku
- Organisations where analysts and data scientists must collaborate on the same pipeline rather than exchanging extractsnot PostgreSQL
- Regulated model risk environments needing documented lineage, sign-off and a record of how a production model was producednot PostgreSQL
- Pushing heavy transformations down into a cloud warehouse while keeping the pipeline definition in one reviewable placenot PostgreSQL
- Large enterprises replacing a sprawl of spreadsheets and unmanaged scripts with something a governance function will acceptnot PostgreSQL
PostgreSQL
- Transaction processingnot Dataiku
- Data storagenot Dataiku
- Application backendnot Dataiku
- Reportingnot Dataiku
- Data analyticsnot Dataiku
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Dataiku
- Visual recipes are stored as Dataiku's own configuration and do not export as runnable SQL or Python, so a Flow with hundreds of visual steps has to be rebuilt from scratch if the organisation ever leaves, and that cost rises with every project added.
- Production requires separate automation and API nodes, each installed and licensed, so the figure quoted for building models is not the figure for running them.
- Licensing is per user across tiers, and the lower tiers are constrained enough that occasional contributors frequently end up needing a full seat, which makes a wide rollout cost more than the initial estimate suggested.
- A self-hosted installation needs a dedicated administrator for upgrades, connection management, permissions and node topology, so the licence is a fraction of the real cost of ownership.
- Computation pushes down to the warehouse or Spark cluster where it is billed by that provider, so a platform sold on making analysts self-sufficient can generate a large warehouse bill that nobody attributes back to it.
PostgreSQL
- Requires manual scaling across multiple machines for very large deployments
- Performance tuning requires deep knowledge of database internals
- No built-in graphical admin interface; command-line tools are primary method
Pricing, plan by plan
Dataiku
Free- Free EditionFree
- Single user
- Core features
- EnterpriseFree
- Full platform
- Collaboration
- MLOps
PostgreSQL
FreeNo published plan breakdown. See the PostgreSQL review.
Which should you pick?
Choose Dataiku if
- You need visual flow.
- You want to start without paying.
- You work on Linux, Mac, Windows, Web.
- You also want visual recipes.
Choose PostgreSQL if
- You need acid compliance.
- You want to start without paying.
- You work on Linux, Windows, macOS, BSD, Unix.
- You also want json/jsonb support.
Questions people ask
- Is Dataiku or PostgreSQL better?
- Neither clearly leads. Dataiku starts at Free and PostgreSQL at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Dataiku or PostgreSQL?
- Dataiku starts at Free and PostgreSQL at Free.
- Does Dataiku or PostgreSQL run on more platforms?
- Dataiku runs on Linux, Mac, Windows, Web. PostgreSQL runs on Linux, Windows, macOS, BSD, Unix.
- Can I use Dataiku for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Dataiku best used for?
- Dataiku is most often used for organisations where analysts and data scientists must collaborate on the same pipeline rather than exchanging extracts, regulated model risk environments needing documented lineage, sign-off and a record of how a production model was produced, pushing heavy transformations down into a cloud warehouse while keeping the pipeline definition in one reviewable place, large enterprises replacing a sprawl of spreadsheets and unmanaged scripts with something a governance function will accept. Of those, organisations where analysts and data scientists must collaborate on the same pipeline rather than exchanging extracts and regulated model risk environments needing documented lineage, sign-off and a record of how a production model was produced are not what PostgreSQL is typically brought in for.
- What can Dataiku do that PostgreSQL cannot?
- Dataiku covers Visual Flow, Visual recipes, Code recipes and notebooks, Computation pushdown. PostgreSQL covers ACID Compliance, JSON/JSONB Support, Full-text Search, Extensibility.
Answered from the vendors’ own pages
Dataiku: Is there a free version?
There is a free edition with limits on users and features, adequate for evaluation and personal work. Anything a team runs in production is a negotiated commercial agreement.
PostgreSQL: Is PostgreSQL completely free?
Yes. PostgreSQL is completely free and open source with no licensing fees or restrictions on use.
SourceDataiku: Do I have to write code to use it?
No. That is the premise. An analyst can build a complete pipeline through visual recipes, and a data scientist can write Python next to it in the same Flow.
PostgreSQL: What platforms does PostgreSQL run on?
PostgreSQL runs on all major operating systems including Linux, Windows, macOS, BSD, and commercial Unix variants, and has been proven highly scalable managing terabytes to petabytes of data.
SourceDataiku: Where does the computation actually run?
Wherever you connect it. Transformations are pushed down into the warehouse, database or Spark cluster where the data lives, which is efficient and also means the compute cost appears on that provider's bill rather than Dataiku's.
PostgreSQL: What procedural languages are supported?
PostgreSQL supports stored functions and procedures in multiple languages including PL/pgSQL, Perl, Python, Tcl, Java, JavaScript, R, and Rust.
SourceDataiku: Can I export my work if we leave?
Code recipes are your code and leave with you. Visual recipes do not export as equivalent code, so the visual portion of a Flow has to be reimplemented, and that portion tends to be the majority in the projects where the platform succeeded best.
PostgreSQL: What is ACID compliance in PostgreSQL?
PostgreSQL has been ACID-compliant since 2001, ensuring data integrity through atomicity, consistency, isolation, and durability guarantees for all transactions.
SourceDataiku: Self-hosted or cloud?
Both are offered. Self-hosting gives control over data residency and networking and requires an administrator; the managed cloud removes that work and moves the constraint to what the vendor's environment supports.
PostgreSQL: Does PostgreSQL support JSON data?
Yes. PostgreSQL supports JSON and JSONB data types for storing and querying JSON documents, along with XML and other document formats.
SourceRelated pages
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- PostgreSQL vs IBM Db2
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- PostgreSQL vs Couchbase
- PostgreSQL vs QuestDB
- PostgreSQL vs FaunaDB
- PostgreSQL vs Firestore
- PostgreSQL vs Amazon Redshift
- PostgreSQL vs Apache Pinot
- PostgreSQL vs DataGrip
- PostgreSQL vs Apache Pulsar
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