Global Trends in the Multimodel Data Platform Market: Key Drivers and Challenges
QKS
Group (formerly Quadrant Knowledge Solutions) Reveals that Multimodel
Data Platform Projected to Register a CAGR of 11.56% by 2028.
A Multimodel
Data Platform is an integrated database system designed to handle multiple data
types and models—such as documents, graphs, and relational data—within a
unified environment, in real-time or near real-time. Unlike traditional
databases that are limited to a specific data model, multimodel platforms allow
users to interact with different data models based on specific business needs
and use cases.
These
platforms empower organizations to manage diverse data models, each requiring
unique data representations, query languages, and containerized environments.
They enable the seamless storage of structured, semi-structured, and
unstructured data within a single database, eliminating the need for data
duplication or migration between systems. This flexibility improves agility,
reduces costs, minimizes data silos, and ensures operational efficiency while
maintaining ease of use, addressing complex data management challenges
effectively.
Key
Questions Explored in This Study:
·
What
is the growth rate of the Multimodel Data Platform market?
·
What
are the major drivers and challenges shaping the global multimodel data market?
·
Which
industries present the highest growth potential during the forecast period?
·
Which
global regions are poised to experience the most significant growth?
·
Which
customer segments offer the greatest potential for multimodel solutions?
·
Which
deployment models for multimodel data platforms will see the fastest adoption
in the next five years?
Strategic
Market Direction:
With the
explosion of data from sources like social media, IoT devices, and sensors,
businesses need platforms capable of managing and analyzing diverse data types
efficiently. These platforms must accommodate a wide range of data—including
graphs, text, images, audio, video, and structured data—without the need for
extensive re-engineering. Multimodel
data platforms provide the flexibility to support emerging data types
and adapt to evolving business demands with minimal redevelopment.
Organizations
increasingly focus on managing structured, unstructured, and semi-structured
data, along with specialized workloads such as geospatial, time-series, graph,
and AI/ML data. Scalability and interoperability are critical factors in
ensuring these platforms can support future data requirements. Additionally,
multimodel platforms streamline the automation of data ingestion, integration,
storage, processing, and access, thereby enhancing productivity for developers
and data engineers.
Vendors
Covered:
ArangoDB,
Couchbase, DataStax, EDB, IBM, InterSystems, MariaDB, MarkLogic, Microsoft,
MongoDB, Neo4j, Oracle, Redis, SAP, and SingleStore.
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