MapR XD Distributed File
and Object Store

Exabyte Scale. Production Ready.

DATASHEET

Ten Reasons Customers Choose MapR XD

MAPR XD DISTRIBUTED FILE AND OBJECT STORE

MapR XD Distributed File and Object Store manages both structured and unstructured data. It is designed to store data at exabyte scale, support trillions of files, and combine analytics and operations into a single platform. MapR XD supports a wide range of workloads, including AI/ML, analytics, and Apache Hadoop. With optimizations for GPU-based workloads, MapR is an ideal platform to run AI/ML/DL pipelines in real time. Integrated with MapR Database and Event Store for Apache Kafka, MapR XD allows users to run nearly any workload on one cluster in production.

MapR XD supports industry standard protocols and APIs, including POSIX, NFS, S3, and HDFS. Support for POSIX means that web servers, containerized applications, and even newer Python-based ML libraries can read and write data directly to MapR. Support for an S3-compatible API means that MapR XD can also serve as the foundation for today’s cloud-native and mobile applications that are increasingly leveraging object storage.

With production-ready capabilities like policy-based data tiering, consistent snapshots, and mirroring, MapR XD serves as the enterprise standard for meeting stringent storage and processing SLAs across on-premises, hybrid cloud, and edge deployments.

WHY MAPR XD DISTRIBUTED FILE AND OBJECT STORE?

CHALLENGES WITH EXISTING TECHNOLOGIES

  • Yesterday’s data management technologies were not designed to take advantage of distributed computing environments, cloud infrastructures, containers and virtualization, and IoT. Additionally, the exponential growth of data volumes and rigid infrastructures make it difficult to move data and integrate analytics with operational processes, effectively creating data silos. These silos make it challenging to derive meaning and intelligence from the data and can lead to high costs of processing and storing data. These costs only increase when data volumes grow.

A BETTER WAY WITH MAPR XD DISTRIBUTED FILE AND OBJECT STORE

  • MapR XD Distributed File and Object Store uniquely overcomes these challenges. Bring data into MapR XD using a simple (and standard) POSIX or NFS interface. Analyze that data in place, saving time and money and minimizing the risk associated with unnecessary data duplication. Deploy MapR to on-premises, the edge, and hybrid cloud environments, while mirroring data across these deployments to solve for pressing data locality and disaster recovery requirements. Consolidate all types of data into a single data platform, while optimizing for cost and performance through policy-based data tiering and volume-based data placement control.

KEY BENEFITS OF MAPR XD DISTRIBUTED FILE AND OBJECT STORE

EXABYTE SCALE

MapR XD can handle trillions of files and thousands of nodes across client hosts, clusters, and racks around the globe. Extend deployments across on- premises, edge, and hybrid cloud environments.

BUILT-IN MULTI-TENANCY

Assign policies such as quotas, data placement, and permissions to logical units of management called volumes. Assign jobs to specific nodes through label-based scheduling.

GLOBAL DATA. ONE VIEW.

With a global namespace, developers, analysts, and data scientists get a unified view of files and objects across the globe without having to be aware of the physical location that data.

PLATFORM-LEVEL SECURITY

Security is built into the platform, not bolted on. Access Control Expressions - Boolean expressions that are far more expressive than POSIX mode bits - can be applied to files and volumes. Audit logs are streamed to MapR Event Store for Apache Kafka, so you won’t lose them.

HIGH-SPEED DATA INGESTION

By exposing the NFS and POSIX interfaces, MapR XD can bring in data from a more diverse set of applications - including legacy ones - at high speed. Using NFS to ingest data also eliminates the need to find and manage ETL tools, which minimizes overall administration and cost.

BALANCE SPEED AND COST

Eliminate difficult questions around storage like “What kind?” and “How much?” MapR XD supports HDDs and flash, and can tier data seamlessly to low-cost S3-compatible object stores. Policy-based data tiering moves data across tiers based on temperature and frequency of use.

WHY MAPR XD MATTERS TO YOU

CIO / ENTERPRISE ARCHITECT

CIO / ENTERPRISE ARCHITECT

  • Meet line of business data needs at lower cost. Grant fast, secure, multi-tenant access to all data for the full spectrum of analytics needs.
  • Accelerate the business. Support in-place ML/AI and analytics, stateful containerized applications, and much more.
  • Deploy anywhere - in the public cloud, on-premises, at the edge, or all of the above at once.
IT / STORAGE ADMINISTRATOR

IT / STORAGE ADMINISTRATOR

  • Built for production. Consistent snapshots, replicas, and mirroring deliver enterprise-grade high availability and disaster recovery.
  • Multi-tenant by design. Assign policies (quotas, permissions, placement) to logical units of management called volumes.
  • Balance cost and performance. Leverage policy-based data tiering, erasure coding, data placement, and more.
DEVELOPERS

DEVELOPERS

  • Persist data for containerized applications. MapR Data Fabric for Kubernetes allows for MapR volumes to be mounted for access by containers.
  • Scale data as containers grow. With a "grow as you go" feature, MapR handles growth in data without it having to be moved to a separate, dedicated environment.
DATA SCIENTISTS

DATA SCIENTISTS

  • Faster time to insight. With support for POSIX, MapR XD works with newer Python-based ML and AI tools like Tensorflow and PyTorch. No need to move the data to a separate cluster.
  • Better support for machine learning logistics. Containerize AI and ML models and train them against all data - not just a subset - leading to more accurate results.

CUSTOMERS USING MAPR XD DISTRIBUTED FILE AND OBJECT STORE

comScore logo
E&J Gallo Winery logo

What's New?