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This update provides the latest microsoft access database engine 2013 free to Microsoft Access Bit Edition. Additionally, this update contains stability and accezs improvements. Details Version:. File Name:. Date Published:. File Size:. Accesd Requirements Supported Operating System.
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Its purpose is to allow applications to store and retrieve data via indexed and sequential access. ESE provides transacted data update and retrieval. A crash recovery mechanism is provided so that data consistency is maintained even in the event of a system crash. ESE caches data intelligently to ensure high performance access to data. In addition, ESE is lightweight making it suitable for auxiliary applications. Microsoft Exchange , up to Exchange shipped with only the bit edition, as it was the only supported platform.
With Exchange , it ships with the bit edition. A database is both a physical and logical grouping of data. An ESE database looks like a single file to Windows. Internally the database is a collection of 2, 4, 8, 16, or 32 KB pages 16 and 32 KB page options are only available in Windows 7 and Exchange , [1] arranged in a balanced B-tree structure.
This information is intermixed within the database file but efforts are made to keep data used together clustered together within the database. An ESE database may contain up to 2 32 pages, or 16 terabytes of data, [3] for 8 kilobyte sized pages.
ESE databases are organized into groups called instances. Most applications use a single instance, but all applications can also use multiple instances. The importance of the instance is that it associates a single recovery log series with one or more databases. Currently, up to 6 user databases may be attached to an ESE instance at any time. A database is portable in that it can be detached from one running ESE instance and later attached to the same or a different running instance.
While detached, a database may be copied using standard Windows utilities. The database cannot be copied while it is being actively used since ESE opens database files exclusively. A table is a homogeneous collection of records, where each record has the same set of columns.
Each table is identified by a table name, whose scope is local to the database in which the table is contained. The amount of disk space allocated to a table within a database is determined by a parameter given when the table is created with the CreateTable operation.
Tables grow automatically in response to data creation. Tables have one or more indexes. There must be at least one clustered index for record data. When no clustered index is defined by the application, an artificial index is used which orders and clusters records by the chronological order of record insertion.
Indexes are defined to persist interesting orders of data, and allow both sequential access to records in index order, and direct access to records by index column values. Clustered indexes in ESE must also be primary, meaning that the index key must be unique. If an insert or update operation causes a page to overflow, the page is split: a new page is allocated and is logically chained in between the two previously adjacent pages.
Since this new page is not physically adjacent to its logical neighbors, access to it is not as efficient. ESE has an on-line compaction feature that re-compacts data. If a table is expected to be frequently updated, space may be reserved for future insertions by specifying an appropriate page density when creating a table or index.
This allows split operations to be avoided or postponed. A record is an associated set of column values. Records are inserted and updated via Update operations and can be deleted via Delete operations.
Columns are set and retrieved via SetColumns and RetrieveColumns operations, respectively. The maximum size of a record is bytes for 8 kilobyte pages with the exception of long value columns. Column types of LongText and LongBinary do not contribute significantly to this size limitation, and records can hold data much larger than a database page size when data is stored in long value columns.
When a long value reference is stored in a record, only 9 bytes of in-record data are required. These long values may themselves be up to 2 gigabytes GB in size. Records are typically uniform in that each record has a set of values for the same set of columns. In ESE, it is also possible to define many columns for a table, and yet have any given record contain only a small number of non-NULL column values. In this sense, a table can also be a collection of heterogeneous records. ESE supports a wide range of columns values, ranging in size from 1-bit to 2 GB.
Choosing the correct column type is important because the type of a column determines many of its properties, including its ordering for indexes. The following data types are supported by ESE:. Each ESE table can define up to fixed length columns, variable length columns and 64, tagged columns.
For a given table, columns fall into one of two categories: those which either occur exactly once in each of the records, with possibly a few NULL values; and those which occur rarely, or which may have multiple occurrences in a single record. Fixed and variable columns belong to the former category, while tagged columns belong to the latter.
The internal representation of the two column categories is different, and it is important to understand the trade offs between the column categories. Fixed and variable columns are typically represented in every record, even when the occurrence has a NULL value.
These columns can be quickly addressed via an offset table. Tagged column occurrences are preceded by a column identifier and the column is located by binary searching the set of tagged columns.
Column types of Long Text and Long Binary are large binary objects. ESE supports append, byte range overwrite, and set size for these columns. Also, ESE has a single instance store feature where multiple records may reference the same large binary object, as though each record had its own copy of the information, i.
Version columns are automatically incremented by ESE each time a record containing this column is modified via an Update operation. This column cannot be set by the application, but can only be read. Applications of version columns include being used to determine if an in-memory copy of a given record needs to be refreshed.
If the value in a table record is greater than the value in a cached copy then the cached copy is known to be out of date. Version columns must be of type Long. Auto increment columns are automatically set by ESE such that the value contained in the column is unique for every record in the table. These columns, like version columns, cannot be set by the application. Auto increment columns are read only, and are automatically set when a new record is inserted into a table via an Update operation.
The value in the column remains constant for the life of the record, and only one auto increment column is allowed per table. Auto increment columns may be of type Long or type Currency. Escrow columns can be modified via an EscrowUpdate operation. Escrowed updates are numeric delta operations. Escrow columns must be of type Long. Examples of numeric delta operations include adding 2 to a value or subtracting 1 from a value.
ESE tracks the change in a value rather than the end value of an update. Multiple sessions may each have outstanding changes made via EscrowUpdate to the same value because ESE can determine the actual end value regardless of which transactions commit and which transactions rollback. This allows multiple users to concurrently update a column by making numeric delta changes.
Optionally, database engine can erase records with zero value of the column. An index is a persisted ordering of records in a table. Indexes are used for both sequential access to rows in the order defined, and for direct record navigation based on indexed column values. The order defined by an index is described in terms of an array of columns, in precedence order. This array of columns is also called the index key. Each column is called an index segment. Each index segment may be either ascending or descending, in terms of its ordering contribution.
Any number of indexes may be defined for a table. ESE provides a rich set of indexing features. One index may be specified as the clustered, or primary, index. In ESE, the clustered index must be unique and is referred to as the primary index. Other indexes are described as non-clustered, or secondary, indexes. Primary indexes are different from secondary indexes in that the index entry is the record itself, and not a logical pointer to the record.
Secondary indexes have primary keys at their leaves to logically link to the record in the primary index. In other words, the table is physically clustered in primary index order. Retrieval of non-indexed record data in primary index order is generally much faster than in secondary index order.
This is because a single disk access can bring into memory multiple records that will be access close together in time. The same disk access satisfies multiple record access operations. However, the insertion of a record into the middle of an index, as determined by the primary index order, may be very much slower than appending it to the end of an index.
Update frequency must be carefully considered against retrieval patterns when performing table design. If no primary index is defined for a table, then an implicit primary index, called a database key DBK index is created. The DBK is simply a unique ascending number incremented each time a record is inserted. As a result, the physical order of records in a DBK index is chronological insertion order, and new records are always added at the end of the table.
If an application wishes to cluster data on a non-unique index, this is possible by adding an autoincrement column to the end of the non-unique index definition. Indexes can be defined over multi-valued columns. Multiple entries may exist in these indexes for records with multiple values for the indexed column.
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