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Head-to-head · Stream Processing Software

Confluent Cloud vs Apache Spark

  • Updated Oct 2026
  • Both researched from official sources
  • 1 check side by side
Higher score Confluent Cloud #6 in Stream Processing Software 8.8/10 Free plan · 30-day trial Free planFree trial✓ 0 of 3 features Try Confluent Cloud
Apache Spark #8 in Stream Processing Software 8.6/10 Free plan Free plan✓ 0 of 3 features Visit Apache Spark

Confluent Cloud leads on 0 checks, Apache Spark on 0, and 1 is even. Who comes out ahead on the 1 yes/no, price and count check where we have data for both products. The editor score weighs everything else too.

Our verdict

  • Highest scoreConfluent Cloud · 8.8/10
  • Free planboth
  • Free trialonly Confluent Cloud

Confluent Cloud scores higher on our rubric for stream processing software: 8.8 against 8.6 out of 10; our editors rank them #6 and #8.

Confluent Cloud is the better fit for enterprises needing managed Kafka and streaming. Apache Spark is the better fit for mature teams combining batch and streaming.

  • Confluent Cloud fits best

    Enterprises needing managed Kafka and streaming

  • Apache Spark fits best

    Mature teams combining batch and streaming

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Side by side

Feature Confluent Cloud 8.8/10 Visit ↗ Apache Spark 8.6/10 Visit ↗
At a glance
Editor score 8.8 8.6
Ranking #6 in Stream Processing Software #8 in Stream Processing Software
Best for Enterprises needing managed Kafka and streaming Mature teams combining batch and streaming
Pricing model Free plan + paid Free
Starting price $385/mo Free plan
Free plan ✓ ✓
Free trial 30 days —
Deployment Cloud Self-hosted
Platforms Web Windows, macOS, Linux
Support Tickets, Community, Docs · 24/7 Community, Docs
Integrations 150+ integrations 20 integrations
Built for Small business, Mid-market, Enterprise Small business, Mid-market, Enterprise
Features Confluent Cloud 0/3 · Apache Spark 0/3
SQL processing Not checked yet Not checked yet
Stateful processing Not checked yet Not checked yet
Event-time windows Not checked yet Not checked yet
Specs
Deployment model Cloud Not checked yet
Supported languages Not checked yet Not checked yet
Source connectors Not checked yet Not checked yet
Our review
Pros
  • Managed Kafka, autoscaling, and 80+ fully managed connectors
  • Schema Registry, governance, TLS, RBAC, ACLs, and SAML/SSO
  • Apache Flink stream processing across AWS, Azure, and Google Cloud
  • Structured Streaming supports incremental stream processing
  • Broad APIs across Python, SQL, Scala, Java, and R
  • Connects to major data sources, clusters, and lakehouse systems
Cons
  • Paid plans start at $385 per month
  • Consumption-based billing varies by region and resource usage
  • Cloud deployment may not suit teams requiring another deployment model
  • Self-hosted deployment requires cluster infrastructure
  • Streaming is one part of a broader batch-focused platform
  • Not a hosted ETL SaaS product with subscription tiers
Our verdict

Confluent Cloud is a cloud-native, fully managed Apache Kafka service for organizations building real-time data pipelines, event-driven applications, streaming analytics, and data integrations. It combines managed Kafka clusters with Kafka…

Read the review →

Apache Spark is an open-source distributed computing engine for large-scale data processing and analytics. It is aimed at developers, data engineers, analysts, and organizations processing data across clusters. Structured Streaming…

Read the review →
  1. Confluent CloudStream Processing Software 8.8Free plan · 30-day trial
  2. Apache SparkStream Processing Software 8.6Free plan

Strengths and trade-offs

  • Confluent Cloud — where it wins

    • Managed Kafka, autoscaling, and 80+ fully managed connectors
    • Schema Registry, governance, TLS, RBAC, ACLs, and SAML/SSO
    • Apache Flink stream processing across AWS, Azure, and Google Cloud

    Where it doesn't

    • Paid plans start at $385 per month
    • Consumption-based billing varies by region and resource usage
    • Cloud deployment may not suit teams requiring another deployment model

  • Apache Spark — where it wins

    • Structured Streaming supports incremental stream processing
    • Broad APIs across Python, SQL, Scala, Java, and R
    • Connects to major data sources, clusters, and lakehouse systems

    Where it doesn't

    • Self-hosted deployment requires cluster infrastructure
    • Streaming is one part of a broader batch-focused platform
    • Not a hosted ETL SaaS product with subscription tiers

More comparisons

All stream processing software comparisons → · Full ranking →

Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

Last updated · How we research and update