Scala vs Apache Spark: What are the differences?
What is Scala? A pure-bred object-oriented language that runs on the JVM. Scala is an acronym for “Scalable Language”. This means that Scala grows with you. You can play with it by typing one-line expressions and observing the results. But you can also rely on it for large mission critical systems, as many companies, including Twitter, LinkedIn, or Intel do. To some, Scala feels like a scripting language. Its syntax is concise and low ceremony; its types get out of the way because the compiler can infer them.
What is Apache Spark? Fast and general engine for large-scale data processing. 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.
Scala and Apache Spark are primarily classified as "Languages" and "Big Data" tools respectively.
"Static typing" is the primary reason why developers consider Scala over the competitors, whereas "Open-source" was stated as the key factor in picking Apache Spark.
Scala and Apache Spark are both open source tools. Apache Spark with 22.5K GitHub stars and 19.4K forks on GitHub appears to be more popular than Scala with 11.8K GitHub stars and 2.75K GitHub forks.
Twitter, Coursera, and 9GAG are some of the popular companies that use Scala, whereas Apache Spark is used by Uber Technologies, Slack, and Shopify. Scala has a broader approval, being mentioned in 437 company stacks & 324 developers stacks; compared to Apache Spark, which is listed in 266 company stacks and 112 developer stacks.
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What is Scala?
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