Nestack's Apache Spark Services
Nestack's Apache Spark services offer advanced parallel development with Python, R, and Scala compatibility.
High-Level Operators and Language Support
Nestack leverages Apache Spark's over eighty high-level operators for easy parallel application development. Spark's compatibility with Python, R, and Scala shells enables interactive use and powers libraries such as DataFrames, SQL, MLib (for machine learning), Spark Streaming, and GraphX for comprehensive analytics solutions.
Seamless Library Integration
With Nestack, you can integrate various libraries within the same application, enhancing the versatility of your big data solutions. Apache Spark's adaptability allows it to run on Mesos, Hadoop, standalone, or in the cloud, with access to diverse data services like Cassandra, S3, HBase, and HDFS.
Exceptional Speed and Efficiency
Nestack's Apache Spark services provide a fast, general engine for large-scale data processing, running programs up to one hundred times faster than Hadoop MapReduce in memory, or ten times faster on disk. This speed is achieved through in-memory computing and other optimizations, making Spark an ideal choice for businesses seeking quick and efficient data processing.
Developer-Friendly and Unified Engine
Apache Spark's easy-to-use APIs and collection of over one hundred operators simplify big data operations. The unified engine comes packaged with higher-level libraries, supporting SQL queries, streaming data, machine learning, and graph processing. These libraries increase developer productivity and can be seamlessly combined to create complex workflows.
Adoption Across Industries
Apache Spark has been rapidly adopted across various industries, including financial services, healthcare, retail, and more. Its ability to provide personalized content, enhance customer experience, and analyze large data sets makes it a versatile tool for different business verticals.