Syncsort APAC Localization Big Data Innovations to Apache Hadoop and Spark
Syncsort, will be delivering the latest capabilities in its industry-leading data integration software, DMX-h v9, in Chinese and Japanese to support growing demand for big data analytics in the Asia Pacific (APAC). The new capabilities allow organizations to access and integrate enterprise-wide data streams on single servers or with Apache Hadoop and Apache Spark, where customers can then leverage advanced analytics for competitive advantage, on-premise and in the cloud.The new release of Syncsort DMX-h supports these use cases by providing organizations with an easy way to securely access and integrate batch and real-time data streams from multiple enterprise data sources, including Kafka, mainframe, relational databases and unstructured sources in the same data pipeline feeding Hadoop and Spark.
With DMX-h v9, a single ETL job can be designed, tested on a local machine and executed in production on Apache Hadoop, MapReduce, Spark, Linux, UNIX and Windows, on-premise or in the cloud. The same job can be moved to a Hadoop cluster, and executed on MapReduce or Spark without any additional design changes or re-compiling. Jobs can be switched from standalone server to MapReduce to Spark by simply selecting the execution framework from a drop-down menu in the graphical user interface. This capability means that businesses who use Syncsort can be confident that data integration applications designed with DMX/DMX-h, existing or new, can be ported to new compute frameworks without requiring any changes. This future-proofs DMX-h applications against the rapid evolution of the Big Data technology stack.
Syncsort’s DMX-h ships with IX, which shortens the time to value for companies implementing big data integration by eliminating the long, expensive man-hours often used for performance tuning. Many data integration tools require a highly skilled developer to spend hours or even days tweaking execution settings and application strategies to get good performance in a particular hardware environment, or for a particular type of workload. DMX-h automatically optimizes application execution based on the selected compute framework at run-time, allowing the user to focus on the job to be done. This not only shortens development time, but also allows the same job to be executed with excellent performance in multiple environments, without any need for manual re-design or re-compiling. This capability dramatically simplifies the process of moving applications from standalone server environments to cluster environments or to the cloud.
Syncsort’s integration with the Kafka distributed messaging systems and MapR Streams allows users to leverage DMX-h’s easy-to- use graphical interface to subscribe, transform and enrich enterprise-wide data coming from real-time sources like sensor data, live transactional data and web stream data. DMX-h’s unrivaled capabilities to access and integrate mainframe data, legacy databases and data from big data repositories such as Hadoop files in the same workflow as streaming sources simplifies the enrichment of streaming data. It allows enterprises to include historical transactional data along with real-time data sources such as mobile and the Internet of Things (IoT). DMX-h can also publish these enriched datasets to Kafka and MapR Streams to simplify the creation of real-time analytical applications by cleansing, pre-processing and transforming data in motion.
Syncsort DMX-h has always had strong support for multi-byte and Unicode encoded data processing, and now in DMX-h v9, it can support any ICU supported code pages. This means that any data, regardless of origin is now available for businesses to use. In addition, localized support for metadata files such as COBOL copybooks simplifies access and integration of previously difficult or unreachable data. With Syncsort DMX-h, all data, regardless of character code set or country of origin is available for integration.