
The BlueData EPIC (Elastic Private Instant Clusters) software platform solves the infrastructure challenges and limitations that can slow down and stall Big Data deployments. With EPIC software, you can spin up Hadoop and Spark clusters – with the data and analytical tools that your data scientists need – in minutes rather than months.
Leveraging the power of containers, BlueData EPIC makes it easier, faster, and more cost-effective to deploy Big Data infrastructure and applications—including Hadoop, Spark, Kafka, Cassandra, and more— whether on-premises or in the public cloud. Your data scientists and analysts can use the tools they prefer. You can run it with any shared storage environment, so you don’t have to move your data. And it delivers the enterprise-grade security and governance that your IT teams require.
With the BlueData EPIC software platform, you can provide a highly flexible and secure Big-Data-as-a-Service environment to enable faster time-to-insights and faster time-to-value – now available either on-premises or on AWS.
Galera Cluster is an open-source, high-availability solution for MySQL and MariaDB that provides true multi-master replication, enabling applications to achieve read and write scalability while ensuring data consistency.
Designed for businesses requiring competitive database systems, Galera Cluster ensures continuous availability through synchronous replication across nodes. Its architecture supports high availability, scalability, and fault tolerance without compromising performance. While focusing on data integrity, it minimizes the overhead typically associated with traditional replication methods, thus enhancing operational efficiency and reducing downtime.
What are the key features of Galera Cluster?In e-commerce, Galera Cluster improves user experiences by handling large volumes of transactions with ease. Financial institutions benefit from its synchronous replication to ensure data accuracy across regions, while online services leverage its high availability to manage user data effectively, preventing losses during peak activities.
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