Apache Spark vs VoltDB: What are the differences?
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.
What is VoltDB? In-memory relational DBMS capable of supporting millions of database operations per second. VoltDB is a fundamental redesign of the RDBMS that provides unparalleled performance and scalability on bare-metal, virtualized and cloud infrastructures. VoltDB is a modern in-memory architecture that supports both SQL + Java with data durability and fault tolerance.
Apache Spark can be classified as a tool in the "Big Data Tools" category, while VoltDB is grouped under "In-Memory Databases".
Some of the features offered by Apache Spark are:
- 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
On the other hand, VoltDB provides the following key features:
- In-Memory Performance with On-Disk Durability
- Transparent Scalability with Data Consistency
- NewSQL – All the benefits of SQL with Unlimited Scalability
"Open-source" is the primary reason why developers consider Apache Spark over the competitors, whereas "SQL + Java" was stated as the key factor in picking VoltDB.
Apache Spark is an open source tool with 22.3K GitHub stars and 19.3K GitHub forks. Here's a link to Apache Spark's open source repository on GitHub.
What is Apache Spark?
What is VoltDB?
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Spark is good at parallel data processing management. We wrote a neat program to handle the TBs data we get everyday.