MapR Database is a high performance NoSQL (“Not Only SQL”) database management system built into the MapR Converged Data Platform. MapR Database is a global multi-model database. It brings together operational applications, analytical applications, real-time streaming, and other workloads to enable next-generation data-intensive applications.
MapR Database is a scalable and reliable database that does not compromise on speed, consistency, and SLA requirements across multiple edge, on-premises, and cloud environments. It is the database for building rich interactive, intelligent (analytics/ML-driven), real-time, and mission-critical applications and running them simultaneously with consistent SLAs.
MapR Database enables a variety of use cases in organizations, including single views of the business, leveraging new types of data such as IOT, list management for all business entities, enabling contextual user experiences with personalization, analytics-as-a-service to enable self-service BI, and intelligent business processes.
MapR Database adds high performance operational database capabilities to the MapR Converged Data Platform.
The native JSON data model and the multimodel flexibility allows developers to choose the appropriate model for a specific use case. As a result, the development process is simplified and time-to-market for new applications and features is reduced. New applications and features can drive significant revenue opportunities for organizations.
In recent benchmarks validated by ESG, MapR Database displayed an average performance improvement of 2.5x more operations/sec than Cassandra and 5.5x more than HBase.
MapR Database is built on the distributed architecture provided by the MapR Converged Data Platform. The distributed foundation underneath MapR Database allows MapR Database to scale effortlessly and linearly. MapR Database scales in many dimensions without limits—PBs of data, hundreds to thousands of nodes, trillions of documents, and millions of tables. Data is automatically sharded, balanced/re-balanced as nodes get introduced or fail—all with no impact to SLAs and no manual intervention by users.
The MapR architecture eliminates single points of failure, avoiding data and job loss even upon multiple node failures in the cluster. Upon node failure, a replica instantly takes over for the failed node without any failover lag. Multimaster, real-time table replication enables distributed applications on global data while reducing the risk for data loss in disaster recovery scenarios.
MapR Database is natively integrated with machine learning and analytical tools to enable advanced analytics, data exploration, and interactive SQL, letting you immediately analyze or process live data and apply machine learning. With in-place analytics and machine learning, you can build and serve ML models and run real-time BI workloads on operational data sets. Large-scale analytics can leverage data in MapR Database and combine it with data in other systems such as Hive Tables, HDFS, and Parquet. MapR Database provides an open API architecture that allows easy integration of third party ML and analytical frameworks that follow standard APIs.
MapR Database is integrated with MapR Event Store out of the box. MapR Event Store is a global event streaming system that enables real-time data ingestion and embedded stream processing. MapR Database in conjunction with MapR Event Store enables simplified data ingestion and ETL as well as allows multiple applications and systems to share information and be synchronized in real-time.
Authentication MapR Database can authenticate users with Kerberos and/or LDAP. MapR offers a standards-based authentication system as a simpler alternative to Kerberos that leverages Linux Pluggable Authentication Modules (PAM) to provide the widest registry support.
Access Control Access Control Expressions (ACEs) control permissions at various levels including column and sub-document by a combination of user, group, and role.
Auditing MapR Database audit logs help to analyze user behavior and meet regulatory compliance requirements. MapR Database uses the JSON format to log accesses at various levels including the column and sub-document levels. MapR also audits at the administrative, authentication, and file levels.
MapR understands that our database architecture is critical to our success and that of our customers. Their system provides the flexibility and integrated analytics required for Xactly to continue to build and scale SPM solutions that are unmatched in performance, scalability, and uptime.
Ron Rasmussen, CTO, Xactly Corporation