Zencluster offers an integrated Apache Spark™ and Apache Cassandra solution, allowing you to use the analytical
power of Spark™ directly where the data is.
Zencluster solution is fully managed by our staff and hosted on Amazon Web Service data centers.Free TrialBook a Demo
APACHE SPARK™: UN MOTORE ANALITICO AD ALTE PRESTAZIONI
Apache Spark™ is the fastest and most powerful Open Source processing engine, built for speed, ease of use and sophisticated analytics.
With an advanced DAG execution engine that supports cyclic data flow and memory calculation, Apache Spark is 100 times faster than competing analytical engines. UC Berkeley’s AMPLab developed Spark in 2009 and released it as Open Source in 2010. Since then it has grown into one of the largest Open Source Big Data communities. Developed by a wide range of developers from more than 200 companies, today it counts the contribution of more than 1000 developers.
APACHE SPARK™ CONSULTING
Our consulting experts, thanks to a deep experience in Big Data Open Source technologies, are ready to assist you in every phase of your applications life cycle. Our consulting services are aimed at those who are considering the adoption of Apache Spark on Cassandra or other Apache technologies. To find out the cost of consulting packages, talk to our consultant.
THE APACHE SPARK ECOSYSTEM
Apache Spark distributed in-memory processing requires a fast back-end and a cluster to provide advanced analytical capabilities: Apache Cassandra is definitely the most modern, reliable and scalable choice to solve the problem.
DATA AND ANALYTICS ENGINES IN THE SAME PLACE
Apache Spark is right where your operational database resides. There is no need to extract, transform and upload data in a new environment.
EFFICIENT AND EASY TO USE
Apache Spark is installed in clusters and can access data from a variety of sources, including Cassandra. It has easy-to-use APIs to operate on large data sets.
A UNIFIED ENGINE
Apache Spark optimally combines various libraries such as Spark SQL, Spark streaming, MLlib (machine learning), GraphX to create complex workflows and manage analysis.