Apache Kylin vs Apache Spark: What are the differences?
What is Apache Kylin? OLAP Engine for Big Data. Apache Kylin™ is an open source Distributed Analytics Engine designed to provide SQL interface and multi-dimensional analysis (OLAP) on Hadoop/Spark supporting extremely large datasets, originally contributed from eBay Inc.
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.
Apache Kylin and Apache Spark can be categorized as "Big Data" tools.
Some of the features offered by Apache Kylin are:
- Extremely Fast OLAP Engine at Scale
- ANSI SQL Interface on Hadoop
- Interactive Query Capability
On the other hand, Apache Spark provides the following key features:
- Run programs up to 100x faster than Hadoop MapReduce in memory, or 10x faster on disk
- Write applications quickly in Java, Scala or Python
- Combine SQL, streaming, and complex analytics
Apache Kylin 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 Apache Kylin with 2.23K GitHub stars and 992 GitHub forks.