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Apache Spark Alternatives
Similar projects and alternatives to Apache Spark
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PostgreSQL
Mirror of the official PostgreSQL GIT repository. Note that this is just a *mirror* - we don't work with pull requests on github. To contribute, please see https://wiki.postgresql.org/wiki/Submitting_a_Patch
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Pandas
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
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Redis
For developers, who are building real-time data-driven applications, Redis is the preferred, fastest, and most feature-rich cache, data structure server, and document and vector query engine.
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Apache Arrow
Apache Arrow is the universal columnar format and multi-language toolbox for fast data interchange and in-memory analytics
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delta
An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs (by delta-io)
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redpanda
Redpanda is a streaming data platform for developers. Kafka API compatible. 10x faster. No ZooKeeper. No JVM!
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Apache Cassandra
Open source transactional distributed database. Linear scalability and proven fault-tolerance on commodity hardware or cloud infrastructure without compromising performance.
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NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better Apache Spark alternative or higher similarity.
Apache Spark discussion
Apache Spark reviews and mentions
Posts with mentions or reviews of Apache Spark.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2026-06-02.
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MLOps Lifecycle: Stages, Workflow, and Best Practices
Feature transformations should be deterministic: The same input should produce the same output when the same feature definition and configuration are applied. This is what allows training, backtesting, and live inference to remain aligned. Tools such as Pandas, Spark, or feature platforms such as Feast can be used to implement that logic.
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7 Free Tools for Data Pipeline Reconciliation and Cross-Source Validation
Apache Spark provides distributed in-memory data processing and is the appropriate tool when the data set to be reconciled does not fit in a single machine's memory, or when parallelizing the comparison across a cluster would reduce runtime from hours to minutes.
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Why Apache IoTDB Is Written in Java: A Decade of Engineering Trade-offs
When IoTDB was initiated in 2011, almost all influential distributed systems and databases were built in Java or on the JVM—such as Hadoop, HBase, Spark (Scala on JVM), Cassandra, Kafka, and Flink. To integrate deeply with the big data ecosystem, choosing Java was a natural decision.
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Apache Spark VS sail - a user suggested alternative
2 projects | 18 Mar 20262 projects | 18 Mar 2026
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I Scraped 47M+ Hacker News Items Into Parquet Files – Here's What I Discovered About HN's Hidden Data Patterns
For handling even larger datasets or building production applications, Apache Spark provides excellent Parquet support with distributed processing capabilities.
- Add Support for PyCapsule to Pyspark
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Pandas 3.0
Funny enough, I actually just (2 weeks ago) added support for streaming from Pyspark to Polars/DuckDB/etc through Arrow PyCapsule. By streaming, I mean actually streaming, not collecting all data at once. It won't be released probably until May/June but it's there: https://github.com/apache/spark/commit/ecf179c3485ba8bac72af...
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Show HN: Spark – Zero-config IoT deployment tool written in Rust
You may want to consider renaming this project.
The name "Spark" already refers to:
A popular data analytics framework of the Apache Foundation: https://spark.apache.org/
A subset of the Ada programming language used for formal verification: https://learn.adacore.com/courses/intro-to-spark/chapters/01...
An Nvidia AI development system: https://www.nvidia.com/en-us/products/workstations/dgx-spark...
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15 AWS EMR Cost Optimization Tips to Slash Your EMR Spending (2025)
AWS EMR (Elastic MapReduce) is a fully managed big data platform. It manages the setup, configuration, and tuning of open source frameworks like Apache Hadoop, Apache Spark, Apache Hive, Presto, and more at scale on AWS infrastructure. EMR handles cluster scaling, resource allocation, and lifecycle management. This allows you to work with large datasets for various use cases, from ETL pipelines to ML workloads. EMR uses a pay-as-you-go pricing model. Costs for compute, storage, and other AWS services can add up quickly as your data grows, clusters get bigger, and jobs become more complex. If you're not careful, costs can skyrocket due to inefficient resource use, poor instance choices, and misconfigured storage. That's why AWS EMR Cost Optimization is key. It helps you get the best performance per dollar while maintaining data processing speed, reliability, and scalability.
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A note from our sponsor - SaaSHub
www.saashub.com | 16 Jun 2026
Stats
Basic Apache Spark repo stats
137
43,440
10.0
6 days ago
apache/spark is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of Apache Spark is Scala.
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Review ☆☆☆☆☆ /10
Wonderful if you need to do a lot of complex or high volume analytics / data pipelines. I recommend going the extra mile and learning Scala, but python is available for those who prefer (wouldn't consider Java or R, but I'm biased).