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What is 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.
Apache Spark pricing
We don't have Apache Spark's full plan breakdown yet (its pricing page resisted automated reading). Here's what we could confirm. Always check live pricing for exact numbers.
What Apache Spark does
The capabilities that matter for data engineering tools, normalised so it lines up with every alternative. “-” means we haven't confirmed it, not that it's missing.
- Tool role
- Processing engine
- Processing paradigm
- Batch + streaming
- Connector count
- -
- CDC / log-based replication
- -
- In-warehouse transformation (push-down)
- -
- dbt-native orchestration
- -
- Self-hosted / open-source available
- ✓
- Managed cloud available
- -
- Data lineage / asset catalog
- -
- Python-first authoring
- -
- Incremental / partition-aware runs
- -
- Built-in data quality / tests
- -
- Horizontal scale (distributed executor)
- ✓
Platform & deployment
Independently observed- CLI
- On-premise
- Self-hosted
Integrations (5)
Independently observed- Hadoop
- HDFS
- YARN
- Kubernetes
- Docker
Security & compliance
Known vulnerabilities: 9 (1 in the last 12 months), max severity CRITICAL sourcea count reflects scale & disclosure, not quality
Apache Spark FAQ
Common questions about Apache Spark, answered from independent, dated evidence.
What is 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. It is indexed under Data Engineering Tools.
Source: https://spark.apache.org
Is Apache Spark free to use?
Apache Spark is open source, so it can be self-hosted and used at no licence cost. It is released under the Apache-2.0 licence. Pricing changes often, so verify at source before relying on it.
Source: https://spark.apache.org
What platforms does Apache Spark support?
Apache Spark supports a command-line interface. Platforms we have not confirmed are simply not listed here rather than ruled out.
Source: https://spark.apache.org
Can Apache Spark be self-hosted?
Yes. Apache Spark can be deployed on-premise and self-hosted, so it does not have to run on the vendor's infrastructure.
Source: https://spark.apache.org
What does Apache Spark integrate with?
We have confirmed 5 integrations for Apache Spark, including Hadoop, HDFS, YARN, Kubernetes and Docker. This is what we could verify from public sources, so the vendor may support others we have not indexed.
Source: https://spark.apache.org
Is Apache Spark open source?
Yes. Apache Spark is published under the Apache-2.0 licence, a permissive licence that generally allows commercial use and modification. Licence terms can change between releases, so verify against the repository for the version you intend to use.
Source: https://github.com/apache/spark
Apache Spark alternatives
Other data engineering tools we track, ranked by the same independent score.
- CensusAutomated data integration platform that moves and transforms data from diverse sources into analytics and AI-ready destinationsmedium · 74%
- Estuary FlowA managed platform for moving data between systems with support for real-time streaming, batch processing, and in-flight transformation.medium · 72%
- HightouchActivate your data warehouse to keep business tools updated with current customer informationmedium · 71%
- Apache AirflowOpen-source workflow orchestration engine for scheduling and monitoring data pipelines as codemedium · 67%
- Prefecthigh · 77%
- Stitchmedium · 70%
Compare Apache Spark
Side by side against other data engineering tools, attribute by attribute, with a source on every value.
The vioscaleAI score: one lens on the evidence
Not user reviews and not a paid placement: a confidence-weighted blend of the independent signals below (adoption, activity, security posture, and more), which you can sort and re-weight yourself. Vendors can correct their listing but can never move their rank, and stars are weighted low as a vanity metric. It is one way to read the evidence for Apache Spark, not the verdict.
| Signal | Score | Weight | Contribution | Evidence |
|---|---|---|---|---|
| Development activity | 63 | 0.09 | 5.9 | ✓ |
| Dependent projects | 66 | 0.06 | 4.1 | ✓ |
| Capabilities | 46 | 0.08 | 3.6 | ✓ |
| Security score | 56 | 0.04 | 2.4 | ✓ |
| Stars | 88 | 0.03 | 2.3 | ✓ |
| Integrations | 22 | 0.07 | 1.6 | ✓ |
| Release cadence | 0 | 0.05 | 0.0 | - |
| Security posture | 5 | 0.07 | 0.0 | - |
| Package downloads | 0 | 0.14 | 0.0 | - |
| Developer Q&A activity | 0 | 0.06 | 0.0 | - |
Computed . Re-weight it by intent, or see the full method.
All data & sourcesshow ↓
Every value we hold, with its source, retrieval date, and confidence. This is the evidence behind the score: don't trust it, verify it.
Activity
| Attribute | Value | Evidence |
|---|---|---|
| Commits last 30d | 100 | mediumsource · 2026-09-10 · 65% |
Adoption
Content
| Attribute | Value | Evidence |
|---|---|---|
| Faq | 6 items | mediumsource · 2026-09-10 · 66% |
Features
| Attribute | Value | Evidence |
|---|---|---|
| Capabilities | Role: engine · Paradigm: both · Self hosted oss: Yes · Distributed executor: Yes | mediumsource · 2026-08-14 · 60% |
Integrations
| Attribute | Value | Evidence |
|---|---|---|
| Count | 5 | mediumsource · 2026-08-14 · 60% |
Language
| Attribute | Value | Evidence |
|---|---|---|
| Primary | Scala | highsource · 2026-09-10 · 90% |
License
| Attribute | Value | Evidence |
|---|---|---|
| Spdx | Apache-2.0 | highsource · 2026-09-10 · 95% |
Market
| Attribute | Value | Evidence |
|---|---|---|
| Availability | PrimaryMarkets: … · AvailabilityScope: global · AvailableCountries: … · NotAvailableCountries: … | highsource · 2026-08-14 · 75% |
Pricing
Security
| Attribute | Value | Evidence |
|---|---|---|
| Disclosure policy | Yes | mediumsource · 2026-08-14 · 60% |
| Scorecard | 5.6 | highsource · 2026-09-10 · 90% |
| Vulnerabilities | Count: 9 · Source: https://advisories.ecosyste.ms/api/v1/advisories?ecosystem=maven&package_name=org.apache.spark%3Aspark-core_2.11&per_page=100 · Last 12m: 1 · Max severity: CRITICAL | highsource · 2026-09-10 · 90% |
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