Apache Spark vs. Hazelcast

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What is Apache Spark?

Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.

What is Hazelcast?

With its various distributed data structures, distributed caching capabilities, elastic nature, memcache support, integration with Spring and Hibernate and more importantly with so many happy users, Hazelcast is feature-rich, enterprise-ready and developer-friendly in-memory data grid solution.
Why do developers choose Apache Spark?
Why do you like Apache Spark?

Why do developers choose Hazelcast?
Why do you like Hazelcast?

What are the cons of using Apache Spark?
No Cons submitted yet for Apache Spark
Downsides of Apache Spark?

What are the cons of using Hazelcast?
No Cons submitted yet for Hazelcast
Downsides of Hazelcast?

Want advice about which of these to choose?Ask the StackShare community!

How much does Apache Spark cost?
How much does Hazelcast cost?
What companies use Apache Spark?
338 companies on StackShare use Apache Spark
What companies use Hazelcast?
32 companies on StackShare use Hazelcast
What tools integrate with Apache Spark?
15 tools on StackShare integrate with Apache Spark
What tools integrate with Hazelcast?
3 tools on StackShare integrate with Hazelcast

What are some alternatives to Apache Spark and Hazelcast?

  • Redis - An in-memory database that persists on disk
  • Memcached - High-performance, distributed memory object caching system
  • Cassandra - Cassandra is a partitioned row store. Rows are organized into tables with a required primary key.
  • Aerospike - Flash-optimized in-memory open source NoSQL database

See all alternatives to Apache Spark

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