Apache Spark vs Google Cloud Dataflow
Side-by-side comparison of features, pricing, and integrations.
Quick Verdict
Apache Spark offers fewer features (12 vs 37) and fewer integrations (4 vs 16). Starting price: Apache Spark at Contact Sales vs Google Cloud Dataflow at Free. Apache Spark has 12 unique features while Google Cloud Dataflow has 37 unique features, with 0 features in common.
| Apache Spark | Google Cloud Dataflow | |
|---|---|---|
| Category | Analytics | Analytics |
| Total Features | 12 | 37 |
| AI-Powered Features | 1 | 8 |
| Starting Price | Contact Sales | Free |
| Pricing Tiers | 0 | 6 |
| Integrations | 4 | 16 |
| Shared Features | 0 | |
| Shared Integrations | 0 | |
| Data Quality | 40% | 85% |
Feature Comparison by Category
AI/ML (0 vs 5)
| Feature | Apache Spark | Google Cloud Dataflow |
|---|---|---|
| Dataflow ML | ||
| MLTransform | ||
| RunInference | ||
| Streaming AI and ML | ||
| Vertex AI Integration |
Analytics (2 vs 1)
| Feature | Apache Spark | Google Cloud Dataflow |
|---|---|---|
| ANSI SQL Support | ||
| Real-time Streaming Analytics | ||
| SQL Analytics |
Billing (0 vs 1)
| Feature | Apache Spark | Google Cloud Dataflow |
|---|---|---|
| Resource-Based Billing |
Cost Optimization (0 vs 1)
| Feature | Apache Spark | Google Cloud Dataflow |
|---|---|---|
| Flexible Resource Scheduling (FlexRS) |
Data Integration (0 vs 3)
| Feature | Apache Spark | Google Cloud Dataflow |
|---|---|---|
| Multi-destination Writing | ||
| Real-time ETL and Data Integration | ||
| Reverse ETL |
Data Processing (2 vs 3)
| Feature | Apache Spark | Google Cloud Dataflow |
|---|---|---|
| Apache Beam SDK Support | ||
| Batch/Streaming Data Processing | ||
| Dataflow Shuffle | ||
| Multimodal Data Processing | ||
| Structured and Unstructured Data Support |
Data Science (1 vs 0)
| Feature | Apache Spark | Google Cloud Dataflow |
|---|---|---|
| Exploratory Data Analysis (EDA) |
Deployment (1 vs 0)
| Feature | Apache Spark | Google Cloud Dataflow |
|---|---|---|
| Docker Support |
Developer Experience (1 vs 0)
| Feature | Apache Spark | Google Cloud Dataflow |
|---|---|---|
| Multi-Language Support |
Development (0 vs 2)
| Feature | Apache Spark | Google Cloud Dataflow |
|---|---|---|
| UDF Builder | ||
| Vertex AI Notebooks Integration |
Engine (1 vs 0)
| Feature | Apache Spark | Google Cloud Dataflow |
|---|---|---|
| Distributed SQL Engine |
Governance (0 vs 1)
| Feature | Apache Spark | Google Cloud Dataflow |
|---|---|---|
| Dataflow Audit Logging |
Infrastructure (1 vs 2)
| Feature | Apache Spark | Google Cloud Dataflow |
|---|---|---|
| Fault-Tolerant Cluster Computing | ||
| Persistent Disk Support | ||
| Snapshot Support |
Installation (1 vs 0)
| Feature | Apache Spark | Google Cloud Dataflow |
|---|---|---|
| PIP Installation |
Machine Learning (1 vs 0)
| Feature | Apache Spark | Google Cloud Dataflow |
|---|---|---|
| Machine Learning |
Monitoring (0 vs 5)
| Feature | Apache Spark | Google Cloud Dataflow |
|---|---|---|
| Data Sampling | ||
| Dataflow Insights | ||
| Job Cost Monitoring | ||
| Rich Monitoring UI | ||
| Straggler Detection |
Performance (1 vs 2)
| Feature | Apache Spark | Google Cloud Dataflow |
|---|---|---|
| Adaptive Query Execution | ||
| Dataflow GPU Support | ||
| Streaming Engine |
Premium Service (0 vs 1)
| Feature | Apache Spark | Google Cloud Dataflow |
|---|---|---|
| Dataflow Prime |
Scalability (0 vs 1)
| Feature | Apache Spark | Google Cloud Dataflow |
|---|---|---|
| Autoscaling |
Security (0 vs 4)
| Feature | Apache Spark | Google Cloud Dataflow |
|---|---|---|
| Confidential VM Support | ||
| Customer Managed Encryption Keys (CMEK) | ||
| Public IP Disable Option | ||
| VPC Service Controls Integration |
Templates (0 vs 1)
| Feature | Apache Spark | Google Cloud Dataflow |
|---|---|---|
| Dataflow Templates |
UI/Development (0 vs 1)
| Feature | Apache Spark | Google Cloud Dataflow |
|---|---|---|
| Dataflow Job Builder |
Use Case (0 vs 3)
| Feature | Apache Spark | Google Cloud Dataflow |
|---|---|---|
| Clickstream Analytics | ||
| Real-time Log Replication and Analytics | ||
| Real-time Marketing Intelligence |
Unique Features
Only in Apache Spark (12)
ANSI SQL Support
SQL Analytics
Batch/Streaming Data Processing
Structured and Unstructured Data Support
Exploratory Data Analysis (EDA)
Docker Support
Multi-Language Support
Distributed SQL Engine
Fault-Tolerant Cluster Computing
PIP Installation
Machine Learning
Adaptive Query Execution
Only in Google Cloud Dataflow (37)
Dataflow ML
MLTransform
RunInference
Streaming AI and ML
Vertex AI Integration
Real-time Streaming Analytics
Resource-Based Billing
Flexible Resource Scheduling (FlexRS)
Multi-destination Writing
Real-time ETL and Data Integration
Reverse ETL
Apache Beam SDK Support
Dataflow Shuffle
Multimodal Data Processing
UDF Builder
Vertex AI Notebooks Integration
Dataflow Audit Logging
Persistent Disk Support
Snapshot Support
Data Sampling
+ 17 more unique features
View Apache Spark details View Google Cloud Dataflow details Apache Spark alternatives Google Cloud Dataflow alternatives
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