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Dynamic Data Store

Describes the Optimizely Dynamic Data Store (DDS), which saves, loads and searches compile-time data types (.NET object instances) and run-time data types (property bags) in shared tables in SQL Server.

The Optimizely Dynamic Data Store (DDS) is an Object-Relational mapper. When used with compile time data types (.NET classes), all properties that have a public getter and a setter (setter does not need to be public) are mapped to a column in a database table. For runtime data types, each property added to a PropertyBag is also mapped in the same way.

DDS is a component offering an API and infrastructure for the saving, loading and searching of both compile time data types (.NET object instances) and runtime data types (property bags) in shared tables in SQL Server. The component is shipped as part of the Framework package.

DDS has the following advantages:

  • Easy to use for simple data structures
  • Supports LINQ for querying data
  • Does not require custom tables, easy to upgrade/install
  • Supports multiple database tables to isolate stores
  • Supports both typed model and property bags
  • Built-in cache

You should not use DDS for high performance and scalability requirements, or when storing very large object graphs (there is no lazy loading support for example). The dynamic nature of DDS might become a bottleneck rather than working in your advantage in these situations and we recommend storing these kind of data in custom tables where the table design and API can be optimized for a specific use case. Alternative technologies for working with database tables in SQL Server include Microsoft’s Entity Framework and NHibernate for .NET.

Map DDS data types

In DDS, data types are stored in one database table. This table contains many columns, several of each data type that the Dynamic Data Store supports. When a data structure is saved, the .NET CLR type of each property is mapped against an internal list of supported types.

The following types of mapping supported:

Map inline

Inline mapping is where a property of a class or PropertyBag can be mapped directly against one of the supported database columns. The following types can be mapped inline:

  • System.Byte (and arrays of)
  • System.Int16
  • System.Int32
  • System.Int64
  • System.Enum
  • System.Single
  • System.Double
  • System.DateTime
  • System.String
  • System.Char (and arrays of)
  • System.Boolean
  • System.Guid
  • EPiServer.Data.Identity

Map collection

A property is mapped as a collection if it implements the System.IEnumerable interface. In this case, all elements of the collection (both keys and values in the case of System.IDictionary) are stored in a special reference table.

Even though the EPiServer.Data.Dynamic.PropertyBag implements System.IEnumerable, it will actually be treated as a reference type (see below).

Map reference

All properties that cannot be mapped inline or as a collection (plus the EPiServer.Data.Dynamic.PropertyBag type) are mapped as references. This means that their properties are mapped in turn as a sub-type, and a link row is added in the reference table to link the parent data structure with the child data structure. This allows for complex trees of data structures (object graphs) to be saved in DDS.

Default table

The default DDS table is called tblBigTable, which contains the following fixed columns (meaning mandatory columns):

  • pkId is the store ID and primary key of each data structure stored.
  • Row is the row index. Each structure may span 1 or more rows in the big table.
  • StoreName is the name of the store the data structure belongs to.
  • ItemType is the .NET CLR Type that contained the properties saved to the current row.

The default big table also contains the following optional columns:

  • BooleanXX (where XX is 01 through to 05) x 5
  • IntegerXX (where XX is 01 through to 10) x 10
  • LongXX (where XX is 01 through to 05) x 5
  • DateTimeXX (where XX is 01 through to 05) x 5
  • GuidXX (where XX is 01 through to 03) x 3
  • FloatXX (where XX is 01 through to 07) x 7
  • StringXX (where XX is 01 through to 10) x 10
  • BinaryXX (where XX is 01 through to 05) x 5
  • Indexed_Boolean01
  • Indexed_IntegerXX (where XX is 01 through to 03) x 3
  • Indexed_LongXX (where XX is 01 through to 02) x 2
  • Indexed_DateTime01
  • Indexed_Guid01
  • Indexed_FloatXX (where XX is 01 through to 03) x 3
  • Indexed_StringXX (where XX is 01 through to 03) x 3
  • Indexed_Binary01 (not Oracle)

The columns whose name starts with Indexed have database indexes created on them.

You may want to add and remove columns in this table to suit the type of data you are saving. This is particularly useful if you are going to store a data type with more than, for example, 10 strings. By default, the 11th to 20th strings would be stored in a 2nd row for the type, which means a join has to be done at runtime when reading the data. By adding String11, String12 and so on to the big table, you limit the chance of a row overspill and therefore increase performance. If you require more indexes, then add columns with names starting with Indexed and make sure an index is created on them.

Add a custom table

You can also add your own table. This is particularly useful if you are going to store a type that only contains strings for example. Along with the mandatory columns (pkId, Row, StoreName, ItemType), you can add about 20 StringXX columns.

Add the EPiServerDataTableAttribute with the TableName property given as the name of the custom table, to use the custom big table.

SQL Server mappings

This table lists the database columns types in the default big table and the .NET CLR “inline” types they are mapped to:

Database Column Type.NET CLR “Inline” Types
varbinary(max)
varbinary(900)
System.Byte[]
intSystem.Byte, System.Int16, System.Int32, System.Enum
bigintSystem.Int64
floatSystem.Single, System.Double
datetimeSystem.DateTime
uniqueidentifierSystem.Guid
nvarchar(max)
nvarchar(450)
System.String, System.Char, System.Char[], EpiServer.Data.Identity
bitSystem.Boolean

Store database views

Each store is actually represented in the database by a view. The views can be used as normal including cross joining with other tables and views in the database.

Assembly and namespaces

The EPiServer.Data assembly contains the following main namespaces:

  • EPiServer.Data namespace contains important classes used in the Dynamic Data Store, most notably the Identity class.
  • EPiServer.Data configuration contains the configuration classes for the Dynamic Data Store.
  • EPiServer.Data.Dynamic namespace contains the DynamicDataStoreFactory and DynamicDataStore classes and their support classes and data structures.

Manage stores

Use the DynamicDataStoreFactory class to create, obtain and delete stores. The class has a single instance which is obtained from the static Instance property. Alternatively, stores can be automatically created for .NET classes by decorating them with the EPiServerDataStoreAttribute and setting the AutomaticallyCreateStore property to true.

See the UsingStores class in the DDS sample project for examples on creating, obtaining and deleting stores.

Save and load data

Data can be saved and loaded using compile time data types (.NET classes) and runtime data types via the EPiServer.Data.Dynamic.PropertyBag class. The Dynamic Data Store is divided into logical stores which are identified by name. Stores are not polymorphic which means only one property set may be saved in a store although it is possible to re-map stores and achieve a level of polymorphism though the use of interfaces and template types.

See the LoadSaveType and LoadSavePropertyBag classes in the the DDS sample project for examples of loading and saving data.

Search data

You can search data in the Dynamic Data Store in the following ways:

  • Simple Find method – Find data structures by matching one or more name-value pairs with data in the store.
  • LINQ – Find data structures using Microsoft’s Language Integrated Query technology.

See the UsingLinq and UsingFind classes in the DDS sample project for examples of searching for data.