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New Data Technologies, Graph Computing and Relationship Discovery in the Enterprise - Carl Olofson

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Presentation slides by Carl Olofso, Research Vice President, Database Management and Data Integration Software for IDC (International Data Corporation).

Presentation slides by Carl Olofso, Research Vice President, Database Management and Data Integration Software for IDC (International Data Corporation).

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  • 1. Graph Computing and Relationship Discovery in the Enterprise
    Carl Olofson
    Research Vice President
    IDC
  • 2. Agenda
    The New Generation of DBMS
    Overview of the movement toward a new generation of DBMS.
    New demands of emerging Cloud-based applications.
    “NoSQL” technologies use cases
    Graph databases
    What they are, and the role they play in social media and various analytical functions.
    List of requirements for a graph database.
    Limitations of RDBMS for handling graph database workloads.
    How an object-oriented DBMS is well suited to use in deploying a graph database.
    Conclusions and Recommendations
    2
    Source:/Notes:
  • 3. A New Generation of DBMS
    Why a new generation of DBMS?
    DBMS users are no longer insisting that one DBMS can handle all workloads.
    New Cloud-based workloads demand different database architectures and technologies.
    Requirements vary:
    Large, informal data collections for ad hoc analysis
    Large, complex data collections for ongoing analysis
    Data sharing for clusters of application servers
    Very large databases (VLDB)
    Extreme transaction throughput
    Rapid execution of complex relational database queries.
    3
  • 4. Third Generation DBMS Technologies
    Relational
    Columnar
    Cellular (or modular)
    In-memory RDBMS
    Non-Relational
    Key-value pair
    List-oriented (Hadoop oriented)
    Graph
    4
  • 5. DBMS Types
    5
    Graph
    Database
    Object
    Database
    Multi-value (Pick style)
    Database
    Data Complexity
    HadoopDatabase
    Relational
    Database
    Network
    Database
    Key-Value Pair
    Database
    Hierarchical
    Database
    Inverted List
    Database
    Model Complexity
  • 6. Web Apps
    Pure OO Apps
    OLTP & DW MF & Dist. Apps
    Graph
    Database
    Object
    Database
    Multi-value (Pick style)
    Database
    MF Transactions, Complex Schema
    DBMS Types and Workloads
    6
    Data Complexity
    HadoopDatabase
    Relational
    Database
    Network
    Database
    High Throughput Mainframe Transactions
    Key-Value Pair
    Database
    Hierarchical
    Database
    Inverted List
    Database
    Model Complexity
  • 7. Most Flexible Relationship Management
    7
    Graph
    Database
    Object
    Database
    Multi-value (Pick style)
    Database
    Data Complexity
    HadoopDatabase
    Relational
    Database
    Network
    Database
    Key-Value Pair
    Database
    Hierarchical
    Database
    Inverted List
    Database
    Model Complexity
  • 8. DBMS Architectures and Workloads
    Different kinds of DBMS being employed to take on workloads required by emerging Cloud-based applications.
    Cloud demands virtualized, limitless data space
    New kinds of data relationships introduced by website constructs and social media, not supported by conventional DBMS
    Fluctuating user demand requires flexible resource scalability in terms of server capacity
    Sometimes, data to be analyzed is dynamically gathered; users chafe at the requirement that they build a schema and map out storage space before they load it.
    8
  • 9. The NoSQL Movement
    9
  • 10. Graph Databases
    A graph database is used to trace relationships among entities, most commonly people, to any depth. Its characteristics are:
    Very simple, fixed schema
    Very complex data relationships
    Used to support complex associations among like entities.
    10
    Jeff Smith
    Attribute(s)
    Nancy Jones
    Jim Smith
    Edge
    Node
    Paul Jones
    Jane Jones-Smith
    Doris Smith
    John Jones
    Meta-Model
    Instance Example (simplified)
  • 11. Requirements for a Graph DBMS
    These are the core requirements of a graph DBMS:
    Must be capable of supporting recursive relationships.
    Must be scalable to arbitrary sizes with minimal administration.
    Provides rapid means of traversing complex relationship structures.
    Can rapidly search many objects based on their relationships and properties.
    For applications such as law enforcement, must have ACID (atomicity, consistency, isolation, durability) properties.
    11
  • 12. Limitations of Relational DBMS
    Why RDBMS does not support graph databases.
    The relational model is flat (2 dimensional).
    A relational database cannot properly capture nested or recursive data.
    Data based on multiple modes of relationship between entities
    Data based on collections of entities of a type under another entity of the same type
    Examples
    Parts database and other “bill of materials” structures
    Employee reporting hierarchy
    Personal relationships captured in social media
    12
    Person-X-Ref
    • Knows-PID (PK)
    • 13. Known-By-PID (PK)
    • 14. Interpersonal-Detail
    Person
    Requires a separate SELECT for each level of query.
  • 17. Object-Oriented DBMS and Graph Databases
    An object-oriented DBMS is well suited to use in deploying a graph database because it can handle the demands of very complex object relationships.
    In order to support the various types of relationships demanded by object-oriented models, OODBMS supports
    Container relationships
    Recursion
    Type hierarchies
    The underlying building blocks needed to support these constructs also enable
    Rapid relationship traversal and search
    Efficient storage of databases of arbitrary size
    13
  • 18. Conclusions and Recommendations
    Conclusions
    A new generation of DBMS is emerging, prompted by new problems posed by Web applications and scalability options inherent in faster, cheaper, more scalable hardware.
    Users are more open to the idea of heterogeneous DBMS; choosing the right tool for the job.
    Graph database is just such a technology, and object technology provides an excellent platform for its management.
    Recommendations
    Now is the time to put appropriate functionality above DBMS uniformity: keep an open mind regarding DBMS products.
    RDBMS does not adequately address all data needs: choose the technology that’s right for the task at hand.
    Graph databases offer relationship tracking and analysis capability that can’t be done by other means. Consider such technology as a solution for such problems in areas such as customer relationship management, social network management, supply chain management, etc.
    14

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