Apache Spark vs Stitch
On the evidence we track, Stitch leads this comparison with a composite score of 68/100. Scores are only directly comparable because these tools share a category; the full breakdown and every source is below.
Capabilities
Feature-by-feature on the axes that matter for data engineering tools. “-” means undocumented, not absent.
What each one is
The product in its own terms, so the numbers below have context.
Apache Spark
Apache Spark is an open-source, multi-language distributed computing engine that unifies data engineering, data science, and machine learning workloads. It processes data at scale using batch or streaming paradigms, provides SQL query capabilities for analytics, and includes built-in libraries for machine learning and graph processing.
Stitch
LeaderAn ELT service that ingests data from 130+ cloud and on-premises applications and data sources, automatically replicating it to data warehouses, data lakes, and lakehouses. It handles extraction, scheduling, monitoring, and loading with minimal configuration required.
Pricing
List pricing as published by each vendor, with the date we read it. Always verify at the source before you buy.
Stitch
LeaderFrom $100/month (Standard, usage-based). 14-day free trial. Annual contracts for Advanced ($18k/year) and Premium ($36k/year).
- StandardFrom $100/month for 5M rows. Usage scales with row volume.
- 7-day historical sync
- 7-day extraction log retention
- SOC 2 Type II compliance
- ISO 27001 compliance
- Notification extensibility
- +8 more
- AdvancedContact sales
- 60-day extraction log retention
- SOC 2 Type II compliance
- ISO 27001 compliance
- Notification extensibility
- Post-load webhooks
- +7 more
- PremiumContact sales
- 60-day extraction log retention
- SOC 2 Type II compliance
- ISO 27001 compliance
- Notification extensibility
- Post-load webhooks
- +7 more
- Stitch PlatformContact sales
- Isolated data pipelines per client
- Advanced settings and features
- 99% uptime SLA
- Mission-critical support
Platform & deployment
Where each product runs and how it can be hosted. A dash means undocumented, not unsupported.
Integrations
What each product connects to. Counts come from the vendor's own integration directory where one exists.
Apache Spark
- Hadoop
- HDFS
- YARN
- Kubernetes
- Docker
Stitch
Leader- Datadog
- PagerDuty
- Slack
- Talend Cloud
- AWS
- Microsoft
- Snowflake
- SAP
- Databricks
- Cloudera
Comparison generated from independently-sourced facts. Every value links to its source and retrieval date. See the method.