Azul Launches Apache Cassandra Consulting Service
Azul Systems taps into the emerging market around Apache Cassandra by providing consulting services for the database.Azul Systems, a provider of Java runtime solutions, recently announced the availability of Cassandra HealthCheck, a new business consulting service designed to help enterprises optimize their Apache Cassandra deployments. The new service helps users eliminate Java-related barriers and improve the runtime consistency, reliability and up-time of their Cassandra deployments. For instance, Azul recently achieved an improvement of more than 56x in worst-case latency, a 25 percent improvement in throughput and a reduction in client disconnects due to node timeouts for a large-scale Cassandra deployment with a customer in the financial services industry. "Many users do not understand the negative impact a Java runtime can have on Cassandra response time, reliability and throughput," said Scott Sellers, CEO and president of Azul Systems, in a statement. "With Azul's Cassandra HealthCheck service offering, our specialists can quickly show enterprises how to maximize the value of their Cassandra investment and eliminate many of the performance and reliability challenges facing Cassandra deployments today. Better Cassandra deployments ultimately mean better business performance." Apache Cassandra is a highly performant, scalable open-source distributed database management system written in Java. Cassandra is designed to handle large amounts of data across many commodity servers, providing high availability with no single point of failure. The system supports clusters spanning multiple data centers.
However, many aspects of Cassandra performance, consistency and availability depend on the capabilities of the underlying Java runtime platform, Azul officials said. Legacy Java Virtual Machines (JVMs) may suffice for some use cases, but enterprises that require highly consistent and reliable low-latency Cassandra deployments are often limited by the JVM itself, specifically the detrimental impact of garbage collection. The Java garbage collection process freezes the application while memory is defragmented and compacted, resulting in random Cassandra pauses that lead to response time inconsistency, increased time to data consistency and can even trigger serious conditions like cascading node failures, where multiple stalled Cassandra nodes trigger cluster-level outages and crashes, Azul said.