Databricks Certifies Apervi Conflux Director TM on Spark.
Apervi, the provider of secure and intuitive big data orchestration platform simplifying data engineering for big data, announced today that Conflux Director TM from Apervi is one of the first Enterprise data engineering Platforms to be certified by Databricks on Apache Spark. Databricks, the company founded by the creators of Spark, recently announced the new Spark Certification as a means to encourage new development on the distributed, in-memory cluster-computing framework.
“End-user applications are critical in enabling enterprises to unlock the true power of a platform, such as Spark, to help deliver deeper insights, faster,” said Arsalan Tavakoli-Shiraji, business development lead, Databricks.
Apervi’s Conflux Director TM, a unified orchestration platform for big data, offers a intuitive code free interface, wherein users can very easily build their big data application workflows in a seamless fashion. By supporting Apache Spark on Conflux, users of Conflux can take advantage of the power of Apache Spark in an intuitive fashion without worrying about learning scala or java. By using Conflux, practically any data engineering challenge can be addressed to execute seamlessly on an Apache Spark cluster, and get accelerated applying comprehensive ETL or ELT transformations on users data in a supercharged fashion. Data engineering is the first stepping-stone to reach the goals of smarter big data analytics to build the next gen Predictive analytics infrastructure and potentially the next Prescriptive analytics infrastructure. Beyond faster ETL, Spark also enables users to build real-time stream processing and high performance processing for implementing faster machine learning processes.
“Our workflows ran much faster in Spark when compared to Hadoop for batch processing. Some of the workflows require processing of the same data and Spark’s in memory computing greatly improves the speeds of these workflows. Spark’s java and scala API’s integrated seamlessly with Conflux. Some of our Customers who are doing batch processing are moving more towards real-time and using Spark greatly helps as it supports both batch and real-time on the same platform. The Spark’s generic DAG model complements Conflux’s DAG model,” said Rajesh Nakkana Chief Architect, Apervi.
“We are very excited to work with Databricks in supporting Apache Spark to increase the adoption and standardization of the Spark platform for our customers,” said Hari Kodakalla, EVP, Apervi.
“Apervi is a terrific example of a pioneering app in the Spark ecosystem and we are thrilled that they are now ‘Certified on Spark’,” said Arsalan Tavakoli-Shiraji, business development lead, Databricks.