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MariaDB vs Amazon Redshift ML

MariaDB logo

MariaDB

Databases

The open source relational database for the enterprise

From
Free
Rated
-
Full reviewWebsite
Amazon Redshift ML logo

Amazon Redshift ML

Machine Learning

SQL statements in Redshift that train models on SageMaker and return them as functions

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: MariaDB jSON support using text fields rather than native binary type; lacks MySQL's JSON syntax and functions; Amazon Redshift ML training is billed by SageMaker separately from Redshift, so a feature that looks like a free SQL statement produces a second line item on a different part of the bill that the analyst who ran it usually cannot see.
  • They diverge on capability: MariaDB covers MySQL Compatibility, Amazon Redshift ML covers CREATE MODEL in SQL.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which MariaDB and Amazon Redshift ML actually diverge.

Attributes where MariaDB and Amazon Redshift ML differ
AttributeMariaDBAmazon Redshift ML
Pricing modelUnknownusage-based
PlatformsLinux, Unix, Windows, macOSWeb
CategoryDatabasesMachine Learning
Founded20092006

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 MariaDB

  • MySQL Compatibility
  • Aria Storage Engine
  • ColumnStore
  • Galera Cluster
  • MaxScale
  • Spider Engine
  • Temporal Tables
  • phpMyAdmin

Only in Amazon Redshift ML

  • CREATE MODEL in SQL
  • Automatic model selection
  • Local inference
  • Bring your own model
  • Algorithm selection
  • Cost ceiling controls
  • Existing warehouse security
  • Batch and interactive scoring

What people use each for

The jobs each tool is most often brought in to do.

MariaDB

  • Transaction processingnot Amazon Redshift ML
  • Data storagenot Amazon Redshift ML
  • Application backendnot Amazon Redshift ML
  • Reportingnot Amazon Redshift ML
  • Data analyticsnot Amazon Redshift ML

Amazon Redshift ML

  • Adding a churn or propensity score to an existing dashboard where the data is already in Redshift and nobody needs a bespoke modelnot MariaDB
  • Letting an analytics team test whether a predictive column has any business value before asking for data science headcountnot MariaDB
  • Scoring rows inside a SQL pipeline where moving data out to a separate service would add fragility for little benefitnot MariaDB
  • Organisations committed to AWS whose main constraint is a data science backlog rather than modelling sophisticationnot MariaDB

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

MariaDB

  • JSON support using text fields rather than native binary type; lacks MySQL's JSON syntax and functions
  • Galera Cluster maximum performance limited to the slowest node in cluster
  • InnoDB tables limited to 1,017 columns and 64 secondary indexes
  • Transaction size limits in Galera (128K rows and 2GB by default)
  • Less strict SQL type checking than PostgreSQL; allows implicit conversions

Amazon Redshift ML

  • Training is billed by SageMaker separately from Redshift, so a feature that looks like a free SQL statement produces a second line item on a different part of the bill that the analyst who ran it usually cannot see.
  • Autopilot searches many candidate models by default and the duration and cost of CREATE MODEL scale with the data size and the MAX_CELLS setting, so an unconstrained statement against a large table is an expensive accident rather than an experiment.
  • Local inference runs on the Redshift cluster itself, so scoring millions of rows competes for the resources the warehouse exists to provide, and the remote inference alternative adds a per-batch network call plus an hourly SageMaker endpoint charge that persists whether or not anyone queries it.
  • The supported problem types are limited to what the exposed algorithms cover, so anything involving text, images, sequences, a custom loss function or a bespoke evaluation metric is out of scope and has to be built conventionally.
  • There is no retraining schedule, drift detection or model registry, so a model created by a statement stays exactly as trained until somebody remembers to recreate it, and nothing in the warehouse will report that its accuracy has decayed.

Pricing, plan by plan

MariaDB

Free

No published plan breakdown. See the MariaDB review.

Amazon Redshift ML

Free
  • Free TrialFree
    • 2-month trial
    • 750 DC2.Large hours
  • On-Demand$0.25/hour
    • Per-node pricing
    • SageMaker training

Which should you pick?

Choose MariaDB if

  • You need mysql compatibility.
  • You want to start without paying.
  • You work on Linux, Unix, Windows, macOS.
  • You also want aria storage engine.
MariaDB review

Choose Amazon Redshift ML if

  • You need create model in sql.
  • You want to start without paying.
  • You also want automatic model selection.
Amazon Redshift ML review

Questions people ask

Is MariaDB or Amazon Redshift ML better?
Neither clearly leads. MariaDB starts at Free and Amazon Redshift ML at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, MariaDB or Amazon Redshift ML?
MariaDB starts at Free and Amazon Redshift ML at Free.
Does MariaDB or Amazon Redshift ML run on more platforms?
MariaDB runs on Linux, Unix, Windows, macOS. Amazon Redshift ML runs on Web.
Can I use MariaDB for free?
Both have a free tier, so you can try either at no cost before committing.
What is MariaDB best used for?
MariaDB is most often used for transaction processing, data storage, application backend, reporting. Of those, transaction processing and data storage are not what Amazon Redshift ML is typically brought in for.
What can MariaDB do that Amazon Redshift ML cannot?
MariaDB covers MySQL Compatibility, Aria Storage Engine, ColumnStore, Galera Cluster. Amazon Redshift ML covers CREATE MODEL in SQL, Automatic model selection, Local inference, Bring your own model.

Answered from the vendors’ own pages

MariaDB: Is MariaDB completely free and open source?

Yes. MariaDB Server is licensed under GPLv2 and guaranteed to remain perpetually free and open source, independent of any commercial entities.

Source
Amazon Redshift ML: Does it require SageMaker?

Yes. Redshift ML is an interface; the training happens in SageMaker and needs an IAM role and an S3 bucket for the intermediate data.

MariaDB: Is MariaDB backward compatible with MySQL?

Yes. MariaDB was designed as a drop-in replacement for MySQL. Every application, driver, and configuration that worked with MySQL works with MariaDB without code changes.

Source
Amazon Redshift ML: Is there an extra charge?

The SQL interface is part of Redshift, but the training runs as a SageMaker job charged at SageMaker rates, and a remote inference endpoint is billed for as long as it exists.

MariaDB: What are the storage engine options in MariaDB?

MariaDB supports multiple storage engines including InnoDB (transactional, default), Aria (crash-safe, good for read-heavy workloads), and MyISAM. The Aria engine is faster than InnoDB for certain read-heavy queries and full table scans.

Source
Amazon Redshift ML: What kinds of model can it build?

Regression, binary and multiclass classification through the automatic path, plus direct use of XGBoost, linear learner, multilayer perceptron and K-means. Anything beyond structured tabular prediction is out of scope.

MariaDB: How much does MariaDB cost?

MariaDB Community Server is completely free to download and use. MariaDB offers paid enterprise support and managed cloud services for organizations needing professional support.

Source
Amazon Redshift ML: Can I use a model I trained myself?

Yes, through the bring-your-own-model path, either compiled into the cluster for local inference or called as a remote SageMaker endpoint.

MariaDB: Does MariaDB support native JSON storage?

MariaDB stores JSON using text fields (the JSON type is an alias for LONGTEXT), not as a native binary type like MySQL does. JSON support exists but is less sophisticated than MySQL's JSON functions and syntax.

Source
Amazon Redshift ML: Does it retrain automatically?

No. Retraining means running CREATE MODEL again, on a schedule you build yourself, and nothing in the product monitors whether it is needed.

MariaDB: What scaling options does MariaDB provide?

MariaDB supports both scaling up (more cores, memory, storage) and scaling out (read replication, Galera Cluster with multi-node replication). However, Galera Cluster performance cannot exceed the slowest node in the cluster.

Source
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