Apache Spark
Apache Spark: A free, self-hosted engine for distributed batch, streaming, SQL, and machine learning workloads. Ranked #12 of 26 in ETL Software by our editors (8.2/10); pricing: Free plan; best for large-scale open-source data processing.
At a glance
- Editor score8.2 / 10
- PricingFree plan
- Best forLarge-scale open-source data processing
- Free planYes
- Paid fromFree
- DeploymentSelf_hosted
- Founded2009
- Facts checked21 Sep 2026
Where it wins
- Distributed batch and streaming processing with Structured Streaming
- Python, SQL, Scala, Java, and R interfaces
- Broad connectivity across files, databases, warehouses, and data platforms
Where it doesn't
- Self-hosted deployment requires cluster and infrastructure management
- More technical than hosted ETL tools for non-developer teams
- No subscription tiers or packaged hosted SaaS experience
Our verdict on Apache Spark
Apache Spark is an open-source distributed computing engine for large-scale data processing and analytics. It is designed for developers, data engineers, analysts, and organizations running workloads across clusters. Spark handles distributed batch processing, incremental stream processing through Structured Streaming, SQL queries, DataFrames and Datasets, machine learning with MLlib, and custom transformations through user-defined functions. It runs on Windows, macOS, and Linux, either locally or on clusters managed by Spark Standalone, Hadoop YARN, or Kubernetes.
The main appeal is breadth within a single processing engine. Teams can work through Python, SQL, Scala, Java, or R interfaces, while connecting to Hive, Avro, Parquet, ORC, JSON, and JDBC sources. Its broader ecosystem includes Apache Kafka, Apache Airflow, Delta Lake, Apache Iceberg, Cassandra, SQL Server, MongoDB, and Elasticsearch. Support for incremental loading, change data capture, custom code, and mixed transformation modes makes Spark suitable for pipelines that extend beyond straightforward batch extraction and loading. MLlib also supports machine learning workloads alongside data preparation and analytics.
Spark’s open-source, free model keeps software licensing separate from the infrastructure needed to operate it. The product is self-hosted rather than a hosted ETL SaaS service, so organizations must choose and manage their deployment environment, including standalone clusters, YARN, or Kubernetes. That model fits teams with engineering capacity and requirements for distributed processing, flexible programming interfaces, or control over execution environments. Organizations seeking a managed interface, guided onboarding, or a packaged subscription service should consider a hosted ETL alternative instead. Spark is the stronger fit when scale, custom transformations, and ecosystem compatibility matter more than low-maintenance operation.
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Apache Spark pricing
Apache Spark fact sheet
| Free plan | Yes |
|---|---|
| Paid from | Free |
| Deployment | Self_hosted |
| Source connectors | Not verified |
| Destination connectors | Not verified |
| Transformation mode | Mixed |
| Incremental loading | Yes |
| Change data capture | Yes |
| Custom code transforms | Yes |
| Deployment | Self-hosted |
| Platforms | Windows, macOS, Linux |
| Support | Community, Docs |
| Built for | Small business, Mid-market, Enterprise (editorial estimate) |
| Integrations | 20 integrations: Hive, Avro, Parquet, ORC, JSON, JDBC … |
| Pricing | Free plan |
| Website | spark.apache.org |
| Facts checked | 21 Sep 2026 |
Apache Spark integrations
Apache Spark lists 20 integrations on its own site.
- Hive
- Avro
- Parquet
- ORC
- JSON
- JDBC
- Apache Kafka
- Kubernetes
- Apache Airflow
- Delta Lake
- Apache Iceberg
- Cassandra
- SQL Server
- MongoDB
- Elasticsearch
- Tableau
- Power BI
- Looker
- Apache Superset
- dbt
Alternatives to Apache Spark
- KeboolaManaged ETL with a free tier, broad connectors, visual orchestration, and hybrid deployment.9.4
- Informatica Data IntegrationA hybrid-ready platform for enterprise ETL, ELT, CDC and orchestration.9.3
- Talend Data FabricA broad, governed platform for complex batch, real-time, and hybrid data environments.9.1
See all Apache Spark alternatives →
Also Ranked In
Apache Spark is ranked in 5 of our directories.
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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