MapR-DB
Data fabric software
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What is MapR-DB
MapR-DB is a distributed NoSQL database that runs on the MapR data platform and is designed to store and serve operational data at scale. It supports both JSON document and wide-column data models and is commonly used for real-time applications, event-driven systems, and analytics-adjacent workloads that need low-latency reads/writes. The product is tightly integrated with the MapR file system and streaming components, emphasizing unified access to data across the platform. MapR-DB is most relevant to organizations already standardized on the MapR/MapR-XD ecosystem or maintaining legacy MapR deployments.
Multi-model NoSQL support
MapR-DB supports both document (JSON) and wide-column access patterns, which can reduce the need to deploy separate databases for different application models. This flexibility helps teams consolidate operational data services when the MapR platform is already in use. It also enables different query and access approaches over the same underlying data depending on workload needs.
Tight platform integration
MapR-DB integrates closely with the MapR file system and related platform services, enabling consistent security, operations, and data access patterns across components. This can simplify data movement and reduce duplication compared with stitching together separate storage and serving layers. For teams building pipelines and applications on the same platform, the integration can lower operational overhead.
Designed for distributed scale
The architecture targets horizontally scalable storage and serving across a cluster, aligning with large-volume, high-throughput operational workloads. This is useful for use cases such as telemetry, clickstreams, and application state where data grows continuously. The distributed design can support locality-aware access patterns when deployed across multiple nodes.
Product lifecycle uncertainty
MapR, the original vendor, was acquired and the MapR product line has undergone transitions, which can create uncertainty about long-term roadmap, support terms, and branding. Buyers may need to validate current ownership, support channels, and release cadence before committing. This risk is higher for net-new deployments than for maintaining existing environments.
Ecosystem and skills niche
MapR-DB is most practical when an organization already runs the MapR platform; otherwise, adopting it can introduce a specialized stack with a smaller talent pool. Compared with more broadly adopted data platforms, hiring and training can be more difficult. Integration patterns and operational tooling may also be less familiar to teams outside the MapR ecosystem.
Limited fabric-layer capabilities
As a database component, MapR-DB does not by itself provide the broader governance, cataloging, lineage, and virtualization features often expected in data-fabric programs. Organizations typically need additional products for metadata management, policy orchestration, and cross-source semantic access. This can increase total solution complexity when the goal is an enterprise-wide data fabric rather than an operational data store.
Plan & Pricing
Pricing model: Consumption-based / term-subscription (licensed by capacity under management or compute units). HPE Ezmeral Data Fabric (MapR lineage) is sold as a consumption/subscription product; specific rates are not published on the vendor website and require contacting HPE Sales.
Free tier/trial: Community Edition (M3) — an unlimited, free, community-supported edition (includes database and streams) is provided; an Enterprise trial license (30-day trial) is available via the My HPE Software Center for evaluation.
Tiers / licensing units (as documented on vendor site):
- Storage tiers (baseline tiers the vendor lists): 1 TB, 10 TB, 100 TB, 1 PB (select a tier when purchasing; over-consumption billed at higher rates).
- Licensing units: capacity under management (measured in TB) and/or compute units (nodes).
- Typical term-subscription cadence: sold as fixed-term subscriptions (commonly 36 months per official licensing document).
Example costs: Not published on HPE official product or docs pages — HPE instructs customers to contact sales for current rates and quotes.
Discounts / overage: Vendor docs note baseline tiers and higher rates when consumption exceeds the selected tier; no public list of volume/commitment discounts — contact HPE Sales.
Notes & purchasing guidance (from official HPE docs):
- Minimum capacity / cluster requirements (documented by HPE): minimum of 5 compute units (nodes) per cluster; minimum capacity for File & Object Store when purchased standalone is 250 TB (HDD) or 100 TB (SSD).
- Licenses are issued/activated via My HPE Software Center; trial licenses (30-day) are available for evaluation.
Seller details
Hewlett Packard Enterprise Company
Spring, Texas, USA
2015
Public
https://www.hpe.com/
https://x.com/HPE
https://www.linkedin.com/company/hewlett-packard-enterprise/
