Apache Spark vs Teradata VantageCloud

Apache Spark8.9Visit TVTeradata VantageCloud8.8Visit

Higher score Apache Spark #4 in Big Data Analytics Software 8.9/10 Free plan Free plan✓ 0 of 1 features Visit Apache Spark

vs

TV Teradata VantageCloud #5 in Big Data Analytics Software 8.8/10 Free plan · pricing on request Free plan✓ 0 of 1 features Visit Teradata

• Apache Spark fits best

  Teams building flexible distributed data pipelines

• Teradata VantageCloud fits best

  Enterprises with governed analytics and ML workloads

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Side by side

Feature	Apache Spark 8.9/10 Visit ↗	TVTeradata VantageCloud 8.8/10 Visit ↗
At a glance
Editor score	8.9	8.8
Ranking	#4 in Big Data Analytics Software	#5 in Big Data Analytics Software
Best for	Teams building flexible distributed data pipelines	Enterprises with governed analytics and ML workloads
Pricing model	Free	Free plan + paid
Starting price	Free plan	$6 usage-based
Free plan	✓	✓
Free trial	—	—
Deployment	Self-hosted	Cloud
Platforms	Windows, macOS, Linux	Web
Support	Community, Docs	Docs
Integrations	20 integrations	7 integrations
Built for	Small business, Mid-market, Enterprise	Enterprise, Mid-market
Features Apache Spark 0/1 · Teradata VantageCloud 0/1
Built-in visualization	Not checked yet	Not checked yet
Specs
Deployment	Not checked yet	Not checked yet
Processing model	Not checked yet	Not checked yet
Documented data scale	Not checked yet	Not checked yet
Data source connectors	Not checked yet	Not checked yet
Query languages	Not checked yet	Not checked yet
Our review
Pros	Processes batch and streaming workloads with SQL and DataFrame APIs Supports Python, SQL, Scala, Java, and R interfaces Runs on Standalone, YARN, or Kubernetes and connects to varied data sources	Combines Teradata Database with elastic, independent compute clusters Supports Apache Iceberg and Delta Lake in cloud object storage Includes in-database analytics, ML, and ModelOps capabilities
Cons	Self-hosted deployment requires teams to manage their environment Not a managed warehouse or hosted ETL service Support is through community resources and documentation	Pricing examples exclude cloud-provider charges Published support channels list documentation only Premier support and advanced services are tied to higher tiers
Our verdict	Apache Spark is an open-source distributed computing engine for large-scale data processing and analytics. Developers, data engineers, analysts, and organizations processing data across clusters can use it for batch workloads, incremental… Read the review →	Teradata VantageCloud is a cloud data warehouse and analytics platform for enterprise organizations, with fit for mixed warehouse, lakehouse, AI, and analytics workloads. It brings together Teradata Database, separate elastic compute… Read the review →

Strengths and trade-offs

• Apache Spark — where it wins

  • Processes batch and streaming workloads with SQL and DataFrame APIs
  • Supports Python, SQL, Scala, Java, and R interfaces
  • Runs on Standalone, YARN, or Kubernetes and connects to varied data sources

  Where it doesn't

  • Self-hosted deployment requires teams to manage their environment
  • Not a managed warehouse or hosted ETL service
  • Support is through community resources and documentation

• Teradata VantageCloud — where it wins

  • Combines Teradata Database with elastic, independent compute clusters
  • Supports Apache Iceberg and Delta Lake in cloud object storage
  • Includes in-database analytics, ML, and ModelOps capabilities

  Where it doesn't

  • Pricing examples exclude cloud-provider charges
  • Published support channels list documentation only
  • Premier support and advanced services are tied to higher tiers

• Apache Spark8.9/10 · Free plan

  Flexible distributed processing for teams building batch and streaming data pipelines.

  Visit Apache SparkFull verdict →
• TVTeradata VantageCloud8.8/10 · Free plan · pricing on request

  A governed cloud analytics platform spanning warehouse, lakehouse, and machine learning workloads.

  Visit TeradataFull verdict →