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Apache SparkOpen-source multi-language engine for data engineering, data science and machine learning.
vs
dbtDeliver trusted data with dbt
Comparison · Data Warehouse · weekly run Nov 3

Apache Spark vs dbt

Which one do AI engines recommend, and how do they differ on price, fit and features?

The short answer

dbt is the stronger AI pick in Data Warehouse: it has a visibility score of 6.5 versus 0.9 for Apache Spark, and ranks ahead in 100% of the answers that name both.

Choose Apache Spark if…

  • Strong distributed processing capabilities for massive workloads
  • Distributes query execution across a cluster of commodity machines

Choose dbt if…

  • You want the brand AI engines rank higher (6.5 vs 0.9)
  • You need a self-hosted or on-premises option
  • You need SOC 2 Type II or ISO 27001:2022 or ISO 27017:2015 or ISO 27018:2025 or ISO 27701:2019 or ISO 42001:2023 or GDPR or CCPA coverage
  • Excellent tool for modern data warehousing

AI visibility side by side

Latest weekly run · Nov 3

Metric Apache Spark dbt
Visibility score0.9%6.5%
Change vs last weekNewNew
Rank in Data Warehouse#26#14
Share of voice0.5%2.3%
Mentions this run313
Positive in AI answers—0%

The stronger value in each row is marked with a ✓.

Visibility score trend

Weekly runs over the last 60 days

0%25%50%75%100%Nov 3Apache Spark 1%

Apache Spark 0pp · dbt 0pp over 0 weekly runs.

Engine by engine

dbt leads on 3 of 3 engines

ChatGPT
1.9%
4.6%
AI Mode
0.9%
7.8%
Perplexity
0%
7%
Apache Sparkdbt

Head to head in AI answers

1 engine answers name both brands

0Apache Spark ranked higher
1dbt ranked higher

Features, pricing & fit

DimensionApache Sparkdbt
Pricing model—Per seat
Entry price—Free; paid from $100 per seat / mo
Free plan—Yes
DeploymentRuns on single machines or on clusters: standalone, Hadoop YARN, Apache Mesos or Kubernetes.Cloud platform, with self-hosted dbt Core and hybrid projects run in the customer's own environment.
Compliance—SOC 2 Type II, ISO 27001:2022, ISO 27017:2015, ISO 27018:2025, ISO 27701:2019, ISO 42001:2023, GDPR, CCPA
Support—Documentation, online learning and community, 24x5 support, Priority support with enhanced SLA, Dedicated account management
Founded2010—
HeadquartersWilmington, Delaware—
Employees5,000+—
Funding—Series D · $414M raised
Best forData engineering, data science and machine learning work on single machines or clusters.Data teams that build SQL-based data transformations and want them tested, version-controlled and governed.

Plans side by side

Apache Spark

Pricing not available.

dbt

Developer$0month
Starter$100user/month
EnterpriseCustomcustom
Enterprise+Customcustom
dbt pricing

Pros and cons

Themes from the AI answers that mention each brand

Apache Spark

  • Strong distributed processing capabilities for massive workloads
  • Distributes query execution across a cluster of commodity machines

    dbt

    • Excellent tool for modern data warehousing
    • Cleans and models raw data into analytics-ready tables
    • Compatible with many other data and BI tools

      Data collected ·ChatGPT, Perplexity, Google AI Mode·coverage 100%·next run

      Cite as: SlateIndex, “Apache Spark vs dbt”, https://slateindex.ai/compare/apache-spark-vs-dbt, data of Nov 3, 2026. Licence: CC BY 4.0.