MapR-DB is a high performance NoSQL (“Not Only SQL”) database management system built into the MapR Converged Data Platform. It is a highly scalable multi-model database that brings together operations and analytics, and real-time streaming and database workloads to enable a broader set of next-generation data-intensive applications in organizations.
Today’s digital economy demands a new way of running business. “Data first” thinking and real-time response are becoming key for organizations to outperform the competition. Organizations are trying to build next-gen applications that provide rich contextual digital user experiences to attract, engage, and retain the customers. They are spending significant efforts on modernizing the core business processes, uncovering real-time insights, and enabling automated decision making to cut down costs and innovate faster.
MapR-DB is an extremely scalable, reliable, globally distributed database. Built into the MapR Converged Data Platform, MapR-DB supports the most stringent speed, scale, and reliability requirements without compromises across multiple edge, on-premises, and cloud environments. It is the NoSQL database for building powerful, intelligent, and mission-critical applications.
Native JSON Simplicity with Expressive Queries
Extreme Performance and Effortless Horizontal Scale
Strong Consistency No Data Loss
Extreme High Availability
Global Multi-Master Replication
Optimized Multi-Tenancy for 1000s of Apps
In-Place SQL and Advanced Analytics/ML
Integrated Streaming for Real-Time Data Ingest, Processing, and Integration
Robust Security and Fine Grained Access Control
The native JSON data model and the multi-model 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.
Personalized and contextual user experience built with MapR-DB can drive higher user engagement and improve net promoter score (NPS). Happy and engaged customers mean less churn, more lifetime customer value, and new products received well by customers.
With in-place analytics and machine learning, MapR-DB enables intelligent applications that can automate decision making in real-time. Organizations benefit from intelligent business processes that require less manual intervention, accelerate decision making, and foster innovation.It also reduces event-to-action cycle with real-time decision making.
MapR-DB is built on the fast, scalable, and reliable foundation provided by the MapR Converged Data Platform. The MapR Platform provides enterprise-grade high availability and disaster recovery for business continuity. The platform also provides snapshots to allow applications to recover from user errors and data corruption.
MapR-DB benefits from the effortless scalability and volume/topology-based multi-tenancy of the underlying platform. Effortless horizontal scale reduces the hardware and administrative expense. Multi-tenancy allows multiple applications to run securely and independently in the same cluster, reducing the hardware cost further.
MapR-DB is integrated with MapR-ES out of the box. MapR-ES is a global event streaming system that enables real-time stream processing embedded in MapR-DB applications. As a result of data being made available and analyzed in real-time using MapR-ES, BI teams across the organization can deliver instant business insights and enable immediate actions.
These applications are fundamental to running a business. For example, fraud prevention is a key process for payment processing. Inventory management, risk analysis, churn detection, and biometric verifications are examples core business applications. Organizations want to build next-gen core applications that support real-time business processes and optimize these business processes using analytics/ML.
Businesses typically use multiple enterprise applications, which means data related to a single business entity can often lie in multiple data silos. “Single view” means providing one place to find all information about a business entity. The most common example of this use case is Customer 360.
Bring all data together in a data hub in real-time to provide real-time business insights. MapR-DB is required for what sounds like a data lake use case due to the frequently changing data from applications and transactional systems. In data lakes, relational data would typically be stored in Parquet or Avro files and accessed through Hive. Parquet is a write-once file format, which means once written, the file cannot be updated. Therefore, frequently changing data can be stored and updated in MapR-DB.
For building analytics-as-a-service, MapR-DB provides ultra low latency performance, effortless scale, and high availability. Many MapR customers report extreme high availability and uptime.
IoT refers to applications that primarily operate on data created by sensors, devices, and machines. The use cases include predictive maintenance, real-time operations dashboards, alerting, real-time tuning of devices, and quality assurance.
This use case involves customizing user experience based on user activity. Common examples include personalized recommendations on video-on-demand services and e-commerce.
This use case consists of catalogs or other metadata used to manage key business entities from enterprises and online services. These entities could be SKUs, inventory parts, sensors, stock trades, playlists, or measurement results.
MapR-DB is an enterprise-grade, high performance, global NoSQL (“Not Only SQL”) database management system. It is a multi-model database that converges operations and analytics in real-time.
Watch: MapR-DB Explainer Video
Brief intro to MapR-DB 6.0 featureset
Watch: MapR-DB 6.0 Demo