Dataware

MapR Executive Perspective

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EXECUTIVE SUMMARY

The fast-paced world of modern frameworks, tools, and applications have one thing in common: data. Data is your most important digital asset. MapR has conceived dataware delivered through the MapR data platform so you can manage your data with any tooling on any infrastructure. Dataware is an abstraction layer that allows data to be managed as a first-class enterprise resource decoupled from any other dependencies. The benefits include much lower TCO for managing data across silos, workloads, and tools and, perhaps more importantly, the ability to gain competitive insights from data even faster.

DATAWARE: MANAGE DATA, NOT POINT-PRODUCT DATA TECHNOLOGIES OR TOOLS

Previous generations of data management were point products or tools solving a specific issue. Conceptually this is similar to networking devices or compute being treated as a manageable resource. Dataware effectively handles the diversity of data types, data access, and ecosystem tools needed to manage data as an enterprise resource regardless of the underlying infrastructure and location. Dataware helps answer pressing questions faced by an enterprise:

  • Where does the data live?
  • What do I know about the data I have?
  • How do I get data to the apps?
  • How do I securely provide data and use it?
  • Am I able to use new tools and techniques easily?

Dataware is a new layer in the enterprise software stack. It solves the challenges of today’s data environment by letting you manage the entire data ecosystem, including multiple clouds and containerized infrastructure. You no longer need to manage multiple data technologies to support distributed applications and analytics across locations. Dataware is powerful for three reasons:

  • The abstraction layer provides a consistent approach for enterprises to manage, secure, govern, and protect data
  • A set of standard APIs enable the consumption of data by a broad set of applications and tools
  • The complexity of data is handled across locations, hardware infrastructures from on-premises to the cloud to the edge, and containers

Dataware optimizes the entire data lifecycle – from ingestion to processing – to enable applications that simultaneously require real-time analytics, machine learning, and AI. Dataware gives complete flexibility in leveraging the underlying infrastructure (on-premises, cloud, or containerized infra- structure) and deployment patterns (hybrid or multi-cloud).

MapR believes that the following are critical capabilities for a new enterprise data layer.

How data is stored:

  • Linear scalability without limits
  • Architected to scale, performance, and consistency to simplify development and management
  • Data and metadata are distributed across dataware to eliminate bottlenecks and points of failure

How data is accessed:

  • Mixed data access from multiple protocols to support broad access and eliminate data duplication and version issues
  • Distributed multi-tenancy to support a wide range of applications and users without compromising on security or performance
  • Global namespace provides data visibility regardless of the actual physical location
  • Integrated data streaming to support real-time and AI workloads

How data is distributed:

  • Distributed location support so data can be located on-premises, in a cloud object store, and at the edge and optimized for costs, capacity, or compliance
  • Location awareness so that management and job execution can be automated and optimized for performance, cost, and compliance
  • Multi-master replication to support distributed operations with transactional integrity

How data is secured:

  • Capability to serve as a long-term system of record
  • Data security and governance within the dataware layer and not a function of the access method or type

MAPR DATA PLATFORM DELIVERS ON THE PROMISE OF DATAWARE

The MapR Data Platform delivers the power of dataware to drive data-driven innovation. MapR envisioned the need for a new data platform built from the ground up to handle a diversity of data types and compute engines to better address the needs of AI and analytics in an increasingly streaming and real-time world. MapR put key technologies essential to achieving high scale and high reliability in a fully distributed architecture that spans on-premises, cloud, and multi-cloud deployments, including edge-first IoT.

DATA PLATFORM

APIs

XD DISTRIBUTED FILE AND OBJECT STORE

DATABASE

EVENT STORE FOR APACHE KAFKA

MAPR CORE SERVICES

DATA PLATFORM

APIs

MAPR CORE SERVICES

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Dataware - MapR Executive Perspective