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Distributed Databases

Distributed Databases. And replication. Definitions. Distributed Database: A single logical database that is spread physically across computers in multiple locations that are connected by a data communications link.

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Distributed Databases

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  1. Distributed Databases And replication

  2. Definitions • Distributed Database: A single logical database that is spread physically across computers in multiple locations that are connected by a data communications link. • Decentralized Database: A collection of independent databases on non-networked computers.

  3. Reasons forDistributed Database • Local business units want control over data. • Consolidate data across local databases for integrated decision making. • Reduce telecommunications costs. • Reduce the risk of telecommunications failures.

  4. Distributed Database Options • Fig. 11-1. (Slide 11-5) • Homogeneous - Same DBMS at each node. • Autonomous - Independent DBMSs. • Non-autonomous - Central , coordinating DBMS. • Heterogeneous - Different DBMSs at different nodes. • Gateways - Simple paths are created to other databases without the benefits of one logical database.

  5. Distributed database environments (adapted from Bell and Grimson, 1992)

  6. Distributed Database Options • Systems - Supports some or all of the functionality of one logical database. • Full DBMS Functionality - All dist. Db functions. • Partial-Multi-database - Some dist. Db functions. • Federated - Supports local databases for unique data requests. • Loose Integration - Local dbs have their own schemas. • Tight Integration - Local dbs use common schema. • Unfederated - Requires all access to go through a central, coordinating module.

  7. Homogeneous, Non-Autonomous Database • Fig. 11-2. • Data is distributed across all the nodes. • Same DBMS at each node. • All data is managed by the distributed DBMS (no exclusively local data.) • All access is through one, global schema. • The global schema is the union of all the local schema.

  8. Focus on The Following Heterogeneous Environment • Fig. 11-3. • Data distributed across all the nodes. • Different DBMSs may be used at each node. • Local access is done using the local DBMS and schema. • Remote access is done using the global schema.

  9. Objectives and Trade-offs • Location Transparency - User does not have to know the location of the data. • Local Autonomy - Local site can operate with its database when central site is down. • Synchronous Distributed Database - All copies of the same data are always identical. • Asynchronous Distributed Database - Some data inconsistency is tolerated.

  10. Advantages ofDistributed Database • Increased reliability and availability. • Local control over data. • Modular growth. • Lower communication costs. • Faster response for certain queries.

  11. Disadvantages ofDistributed Database • Software cost and complexity. • Processing overhead. • Data integrity exposure. • Slower response for certain queries.

  12. Options forDistributing a Database • Data replication. • Horizontal partitioning. • Vertical partitioning. • Combinations of the above.

  13. Data Replication • Advantages - • Reliability. • Fast response. • May avoid complicated distributed transaction integrity routines (if replicated data is refreshed at scheduled intervals.) • De-couples nodes (transactions proceed even if some nodes are down.) • Reduced network traffic at prime time (if updates can be delayed.)

  14. Data Replication • Disadvantages - • Additional requirements for storage space. • Additional time for update operations. • Complexity and cost of updating. • Integrity exposure of getting incorrect data if replicated data is not updated simultaneously. • Therefore, better when used for non-volatile data.

  15. Types of Data Replication • Snapshot Replication - • Changes are periodically sent to a master site which sends an updated snapshot out to the other sites. • Near Real-Time Replication - • Broadcast update orders without requiring confirmation. • Pull Replication - • Each site controls when it wants updates.

  16. Issues in Data Replication Use • Data timeliness. • Useful if DBMS cannot reference data from more than one node. • Batched updates can cause performance problems. • Updates complicated with heterogeneous DBMSs or database design. • Telecommunications speeds may limit mass updates.

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