Apache Spark vs Materialize: Which Should You Choose in 2026?
Choosing between Apache Spark and Materialize comes down to understanding what each tool does best. This comparison breaks down the key differences so you can make an informed decision based on your specific needs, not marketing claims.
By Toolradar Team · Last updated February 22, 2026 · Methodology
Short on time? Here's the quick answer
We've tested both tools. Here's who should pick what:
Apache Spark
Unified analytics engine for big data
Best for you if:
- • You need data visualization features specifically
- • Apache Spark is a multi-language engine for large-scale data engineering, data science, and machine learning.
- • It supports batch and real-time streaming data processing, SQL analytics, and scales from single-node machines to clusters.
Materialize
The Live Data Layer for Apps and AI Agents, enabling real-time insights with SQL.
Best for you if:
- • You want the higher-rated option (7.1/10 vs 0.0/10)
- • You need big data analytics features specifically
- • Provides a live data layer for real-time applications and AI agents.
- • Processes data streams and allows querying fresh data using standard SQL.
| At a Glance |  Apache Spark |  Materialize |
|---|---|---|
Price | Paid | Paid |
Best For | Data Visualization | Big Data Analytics |
Rating | —/100 | 71/100 |
| Feature | Apache Spark | Materialize |
|---|---|---|
| Pricing Model | Open_source | Paid |
| Editorial Score | — | 71 |
| Community Rating | No ratings yet | No ratings yet |
| Total Reviews | 0 | 0 |
| Community Upvotes | 145 | 0 |
| Categories | Data VisualizationETL & Data Pipelines | Big Data AnalyticsBusiness Intelligence |
How Apache Spark and Materialize Compare
Apache Spark
Unified analytics engine for big data
Paid
Materialize
The Live Data Layer for Apps and AI Agents, enabling real-time insights with SQL.
Paid · 71/100 score
Apache Spark is a data visualization tool. Materialize is in big data analytics.
Who Should Use What?
On a budget?
Both are open_source. Compare plans on their websites.
Go with: Materialize
Want the highest-rated option?
Materialize scores 71/100. Apache Spark is unrated.
Go with: Materialize
Value user reviews?
Neither has user reviews yet.
Go with: Materialize
3 Questions to Help You Decide
What's your budget?
Apache Spark is open_source. Materialize is paid.
What's your use case?
Apache Spark is a data visualization tool. Materialize is in big data analytics. Pick the category that matches your needs.
How important are ratings?
Not all tools have been rated yet.
Key Takeaways
Materialize
- Higher score: 71/100 vs unrated
- Our pick for this comparison
Apache Spark
- More community upvotes (145)
- Better fit for data visualization
The Bottom Line
Materialize (71/100) is our pick.
Frequently Asked Questions
Is Apache Spark or Materialize better?
Materialize scores 71/100 in our evaluation. Apache Spark is open_source and Materialize is paid.
What are Apache Spark and Materialize used for?
Apache Spark: Unified analytics engine for big data. Materialize: The Live Data Layer for Apps and AI Agents, enabling real-time insights with SQL..
What does Apache Spark cost vs Materialize?
Apache Spark is a paid tool. Materialize is a paid tool. Visit their websites for detailed pricing.