Technology · head to head
Postgres vs Apache Spark
A
Apache Spark
Technology
A multi-language engine for data engineering, data science, and machine learning
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Postgres each major version is supported for only 5 years after its initial release, after which it is end-of-life; Apache Spark licensed under Apache License 2.0 per spark.apache.org; as open source software it has no paid tier or vendor price to compare
Where they differ
Only the attributes on which Postgres and Apache Spark actually diverge.
| Attribute | Postgres | Apache Spark |
|---|---|---|
| Platforms | Linux, Windows, Macos, Docker | Web |
| Founded | 1996 | Unknown |
Identical on both: starting price (Free), pricing model (open-source), free tier (Yes), user rating (Not yet rated), category (Technology).
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 Postgres
- ACID compliance
- Complex queries
- Foreign keys
- Triggers
- Views
- Stored procedures
- JSON/JSONB support
- Full-text search
Only in Apache Spark
Nothing recorded that Postgres does not also cover.
What people use each for
The jobs each tool is most often brought in to do.
Postgres
- Running a general purpose relational database for applicationsnot Apache Spark
- Self-hosting an open source SQL database with no licence feenot Apache Spark
- Workloads needing extensions, JSON and full text search in one enginenot Apache Spark
Apache Spark
No use cases recorded yet. See the Apache Spark review.
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Postgres
- Each major version is supported for only 5 years after its initial release, after which it is end-of-life
- Major version upgrades break on-disk compatibility and require a full dump and reload or the pg_upgrade tool
- New major versions ship about once a year, so staying supported means a disruptive upgrade cycle
- Minor releases contain only frequently-encountered bug fixes, low-risk fixes, security issues and data corruption fixes, so feature gaps are not addressed within a major version
- There is no vendor SLA; commercial support must be bought separately from third party professional services listed by the project
Apache Spark
- Licensed under Apache License 2.0 per spark.apache.org; as open source software it has no paid tier or vendor price to compare
- Installation on a laptop requires pip install pyspark or a Docker image per spark.apache.org; there is no hosted single-click deployment offered by the Apache project itself
Pricing, plan by plan
Postgres
Free- Community EditionFree
- Full database features
- No limitations
- Community support
Apache Spark
FreeNo published plan breakdown. See the Apache Spark review.
Which should you pick?
Choose Postgres if
- You need acid compliance.
- You want to start without paying.
- You work on Linux, Windows, Macos, Docker.
- You also want complex queries.
Questions people ask
- Is Postgres or Apache Spark better?
- Neither clearly leads. Postgres starts at Free and Apache Spark at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Postgres or Apache Spark?
- Postgres starts at Free and Apache Spark at Free.
- Does Postgres or Apache Spark run on more platforms?
- Postgres runs on Linux, Windows, Macos, Docker. Apache Spark runs on Web.
- Can I use Postgres for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Postgres best used for?
- Postgres is most often used for running a general purpose relational database for applications, self-hosting an open source sql database with no licence fee, workloads needing extensions, json and full text search in one engine. Of those, running a general purpose relational database for applications and self-hosting an open source sql database with no licence fee are not what Apache Spark is typically brought in for.
- What can Postgres do that Apache Spark cannot?
- Postgres covers ACID compliance, Complex queries, Foreign keys, Triggers.