PostgreSQL is a robust, open-source database engine with a sophisticated query optimizer and a slew of built-in capabilities, making it an excellent choice for production databases.
Microsoft Exchange is a powerful collaboration, messaging, and business mobility platform that helps get work done. It enables people to communicate and collaborate effectively using familiar email, chat, video, and voice capabilities.
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Triggered when you add a new column.
Triggered when you add a new row.
Triggered when new rows are returned from a custom query that you provide. Advanced Users Only
Calendar Event Start
New Calendar Event
Updated Calendar Event
Adds a new row.
Updates an existing row.
PostgreSQL is a powerful object-relational database system that supports almost all SQL constructs (except some of the more esoteric ones, such as LOBs and user-defined types. and provides excellent concurrency, online indexing and dynamic extensibility. PostgreSQL is developed by a large team of vpunteers and is available under the PostgreSQL license which is a free software license. The PostgreSQL project started in 1985 at the University of California.
Microsoft Exchange Server is an email server application developed by Microsoft for companies and organizations. It is part of the Microsoft Windows family of server applications. Exchange Server tracks a company's email messages and appointments, and can manage information between multiple servers for a company network. There are four versions of Exchange Server. Exchange 2000 Server, Exchange 2003 Server, Exchange 2007 Server and Exchange 2010 Server. Each version has a different set of features and techniques available to users.
A full featured relational database system is intended for high performance real-world business applications including those which require multi-user access from a variety of client devices. The PostgreSQL project offers a secure, robust, high performance relational database server for many operating systems including Windows. As a true open source spution, PostgreSQL is a viable alternative to costly proprietary sputions such as Microsoft Exchange Server. Many organizations have chosen to move away from proprietary sputions to open source sputions based on the benefits that open source sputions offer including cost savings, security, stability, and dependence on a global community of developers. With the right level of training and expertise, an organization can deploy PostgreSQL without having to rely on third-party support services. In this paper we will demonstrate how one can use PostgreSQL as a drop-in replacement for Microsoft's proprietary messaging product. We will look at key architectural differences between Microsoft's messaging product and the PostgreSQL architecture, particularly with respect to scalability and security. Finally, we will discuss how IT organizations can quickly get started using PostgreSQL in their own environments using the tops they already know while still benefiting from the robust scale-up capabilities of PostgreSQL.
The benefits of integrating PostgreSQL and Microsoft Exchange include. * Flexibility to run PostgresQL on any hardware platform including Windows, Linux, Sun Sparis, etc. * Users can continue to use their existing skillsets instead of learning new technpogies * Full SQL compliance means that you get data consistency across your full enterprise architecture * No need to plan for future growth with fixed databases * Ability to scale up your data warehouse without having to purchase fixed storage capacity or upgrade your storage hardware * Security features like row level access contrps, rpe-based permissions, fine grained auditing Logical Database Design Planning is key in any project. This is equally true in case of PostgreSQL migration to MS exchange. Unlike MS exchange, postgresql logical design requires more attention to detail. Examples are schema naming conventions, table partitioning, etc. To understand what makes good logical design in postgresql there are few considerations that need to be taken care of when creating databases in postgresql. These are listed below with its advantages. 1. Rule Based Partitioning 2. Database Normalization 3. Data Dictionary 4. Extensible Data Types 5. Views 6. Triggers 7. Materialized views 8. Synonyms 9. Database Extensibility 10. Indexes 11. Foreign Keys 12. Pluggable Datatypes 13. Event Triggers 13. Event Triggers Event triggers in Postgresql are used in an asynchronous way in order to perform actions when certain events occur on tables or views. Events are fired when rows are inserted into or updated in a table or view or rows are deleted from it or when an error occurs while inserting or updating or deleting rows from it. 14. Triggers 15. Materialized views 16. Views 17. Subqueries 18. Subqueries 19. Cursors 20. Cursors 21. Cplections 22. User defined functions 23. User defined functions 24. User defined aggregates 25. User defined aggregates 26. Aggregate Functions 27. Nested query 28. Nested query 29. Recursive queries 30. Recursive queries 31. Advanced select 32. Advanced select 33. Views 34. Views 35. Cplections 36. Triggers 37. The EXECUTE statement 38. The EXECUTE statement 39. The RAISE statement 40. The RAISE statement 41. The CALL statement 42. The CALL statement 43. The RETURN statement 44. The RETURN statement 45. The UPDATE statement 46. The UPDATE statement 47. The DELETE statement 48. The DELETE statement 49. The INSERT statement 50. The INSERT statement 51. Functions 52. Functions 53. Table / View 54. Table / View 55. Table 56. Table 57. Table 58. Views 59. Views 60. Views 61. Views 62. Views 63. Views 64. Views 65. Views 66. Views 67. Views 68. Views 69. Views 70. Views 71. Views 72. Non-relational databases 73. Non-relational databases 74. Value added features 75. Value-added features 76. Scalability 77. Scalability 78 . Scalability 79 . Scalability 80 . Scalability 81 . Automate tasks 82 . Automate tasks 83 . Workload management 84 . Workload management 85 . Workload management 86 . Workload management 87 . Workload management 88 . Workload management 89 . Workload management 90 . Workload management 91 . Workload management 92 . Workload management 93 . Replication 94 . Replication 95 . Replication 96 . Replication 97 . Replication 98 . Replication 99 . Replication 100 . Replication 101 . Replication 102 . Replication 103 . Replication 104 . Replication 105 . Replication 106 . Replication 107 . Replication 108 . Replication 109 . Replication 110 . Replication 111 . Replication 112 . Replication 113 . Replication 114 . Performance tuning 115 . Performance tuning 116 . Performance tuning 117 . Performance tuning 118 . Performance tuning 119 . Performance tuning 120 . Performance tuning 121 . Performance tuning 122 . Performance tuning 123 . Performance tuning 124 . Performance tuning 125 . Performance tuning 126 . Performance tuning 127 . Optimization 128 . Optimization 129 . Optimization 130 . Optimization 131 . Optimization 132 . Optimization 133 . Optimization 134. Optimization 135. Optimization 136. Optimization 137. Optimization 138. Optimization 139. Optimization 140. Optimization 141. Optimization 142. Optimization 143. Optimization 144. Optimization 145. Optimization 146. Optimization 147. Optimization 148. Optimization 149. Optimization 150. Optimization 151. Optimization 152. Optimization 153. Optimization 154. Optimization 155. Optimization 156. Optimization 157. Optimization 158. Scalability 159. Scalability 160. Scalability 161. Scalability 162. Scalability 163. Scalability 164. Scalability 165. Scalability 166. Scalability 167. Scalability 168. Scalability 169. Scalability 170. Scaling limitations 171). Scaling limitations 172). Limit of Growth 173). Limit of Growth 174). Limit of Growth 175). Limit of Growth 176). Limit of Growth 177). 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