Glossary of Major Delphix Concepts

A generic term for Delphix virtualized objects from which you can create virtual databases (VDBs).

A dataset can be a dSource, VDB, or vFiles.

The system, typically an RDBMS, that feeds information to the Delphix Engine, and from which virtual objects are derived. A data source can be a database, an application, or a set of unstructured files.

Not to be confused with a dSource, which is a virtualized, compressed duplicate of this database. (See below.)

Object groups are arbitrary collections of dSources or VDBs used for organization.

Note: Objects cannot be moved between groups.

Is an object on the Delphix Engine that is a virtualized representation of a database that the Delphix Engine uses to create and update virtual copies of your database. As a virtualized representation of your source data, it cannot be managed, manipulated, or examined by database tools. Because dSources are simply source data, you must provision a VDB in order to distribute/clone/test the data being pulled in. VDBs can also later be refreshed from the same or other points in time synced from the dSource.

Connection details, host information, and data source information for Delphix to communicate with a host or cluster.

A standalone program which validates that host machines are configured correctly before the Delphix Engine uses them for syncing from data sources or provisioning VDBs.

HostChecker is a Delphix script that you should run before adding any Environment to your Delphix Engine. It is available to download from the HostChecker subfolder at download.delphix.com.

Copies of the source Delphix Engine information on the target Delphix Engine, which can include objects such as dSources, VDBs and vFiles. Replicas preserve object relationships and naming nomenclatures. Replicas do noot copy platform specific configurations such as users, permissions etc.

You can replicate datasets between two instances of the Delphix Engine. Replication consists of a profile-replica pair. It is configured on the source Delphix Engine and copies specified objects to a target Delphix Engine. The source engine then sends incremental updates manually or according to a schedule. In addition, you can provision VDBs from replicated objects, allowing for geographical distribution of data and remote provisioning.

Snapshots represent the state of a dataset at a specific moment in time. They accumulate over time from policies or are generated by manual creation. Snapshots allow you to choose a point in time from which to provision, refresh, or rollback.

If you have LogSync enabled, you can provision refresh or rollback from a point in time between the snapshots endpoints.

Note: Point in time provisioning is also dependent on log retention.

The standard process for importing data from a linked source into the Delphix Engine. An initial SnapSync is performed to create a dSource on the Delphix Engine. Incremental SnapSyncs are performed to provide additional points in time to the dSource on the Delphix Engine.

The original (either physical or virtual) database. It is commonly a production database, although it could be any database that the user designates as a source. Delphix creates a dSource from the source database.

Virtual unstructured files. A virtual copy of data files created and managed by Delphix. vFiles are fully functional read/write copies of the original unstructured files source. You can mount vFiles across one target environment or several.

Rewinding a VDB rolls it back to a previous point in its Timeflow. The VDB will no longer contain changes that occurred after the rewind point. This also creates an alternative Timeflow.

Access statistics on the dSource, VDB, or Snapshot such as usage, history, and space consumption

Access statistics on all dSources, VDBs, or Snapshots in the group such as usage, history, and space consumption

• Access statistics on the dSource, VDB, or Snapshot such as usage, history, and space consumption
• Provision VDBs from owned dSources and VDBs

• Access statistics on all dSources, VDBs, or Snapshots in the group such as usage, history, and space consumption
• Provision VDBs from all dSources and VDBs in the group

• Provision VDBs from owned dSources and VDBs
• Perform Virtual to Physical (V2P) from owned dSources
• Access the same statistics as an Reader
• Refresh or Rollback VDBs
• Take Snapshots of dSources and VDBs

• Provision VDBs from all dSources and VDBs in the group
• Refresh or Rollback all VDBs in the group
• Snapshot all dSources and VDBs in the group
• Perform Virtual to Physical (V2P) from owned dSources
• Apply custom policies to dSources and VDBs
• Create template policies for the group
• Assign Owner privileges for dSources and VDBs
• Access the same statistics as an Provisioner, Data Operator, or Reader

• Access statistics on the dSource, VDB, or snapshot such as usage, history, and space consumption
• Refresh or rollback VDBs

• Access statistics on all dSources, VDBs, or snapshots in the group such as usage, history, and space consumption
• Refresh or rollback all VDBs in the group

Has full access to all report data and can configure and administer Delphix Self-Service. Additionally, can use the Delphix Engine to:

• add/delete reports
• add/delete users
• change tunable settings
• add/delete tags
• create and assign data templates and containers

A logical reference to a point in time on a branch. You can use it as a point from which to fork new branches. It can also be the target of policies – for example, you can arrange to keep this bookmark for two years.

Bookmarks are a way to mark and name a particular moment of data on a timeline. You can restore the active branch's timeline to the moment of data marked with a bookmark. You can also share bookmarks with other Delphix Self-Service users, which allows them to restore their own active branches to the moment of data in your container. The data represented by a bookmark is protected and will not be deleted until the bookmark is deleted.

Branches are task-specific groupings you can create within a data container. A branch is used to track a logical task, and contains a timeline of the historical data for that task. As you work within your data container, you can create more branches over time to run or complete separate tasks.

Branches represent a logical sequence of activity, separate from the underlying data lineage. This is the main concept introduced in the core engine and forms the basis of many higher level primitives. Branches:

• Can have only one timeline active at any time
• Can be user-visible (e.g. exported to a user target) or implementation (e.g. just a staging source to run a series of transformations)

Consists of one or more Data Sources, such as databases, application binaries, or other application data. Allows users to:

• Undo any changes to their application data in seconds or minutes

• Have immediate access to any version of their data over the course of their project

• Share their data with other people on their team, without needing to relinquish control of their own container

• Refresh their data from production data without waiting for an overworked DBA

Admin users have full access to all report data and can configure the Delphix Reporting appliance. (They can also assign auditor users a set of tags to restrict which report data they can view. There is no default auditor account. The first Delphix Administrator will need to create the auditor users and will be responsible for creating their User IDs and Passwords.)

An Admin user can:

• Add/delete reports
• Add/delete users
• Change tunable settings
• Add/delete tags

Reports present aggregated data across all connected Delphix Engine .

Interactive reports such as Storage Breakdown and History display interactive graphical representations of historical and current storage usage across all Delphix Engines you are monitoring. These visualizations of storage and disk capacity enable you to analyze and mediate storage across Delphix Engines from multiple perspectives.

Allows you to state what values will replace the original data. There will be no collisions in the masked data, because it always matches the same input to the same output. For example “David” will always become “Ragu,” and “Melissa” will always become “Jasmine.” The algorithm checks whether an input has already been mapped; if so, the algorithm changes the data to its designated output. You can use a Mapping Algorithm on any set of values, of any length, but you must know how many values you plan to mask.

The only type of algorithm that allows you to reverse its masking. For example, you can use a tokenization algorithm to mask data before you send it to an external vendor for analysis. The vendor can then identify accounts that need attention without having any access to the original, sensitive data. Once you have the vendor’s feedback, you can reverse the masking and take action on the appropriate accounts.

Like mapping, a tokenization algorithm creates a unique token for each input such as “David” or “Melissa.” The Delphix Engine stores both the token and the original so that you can reverse masking later.

Helps remove sensitive data that appears in free-text columns such as “Notes.” This type of algorithm requires some expertise to use, because you must set it to recognize sensitive data within a block of text.

One challenge is that individual words might not be sensitive on their own, but together they can be. The algorithm uses profiler sets to determine what information it needs to mask. You can decide which expressions the algorithm uses to search for material such as addresses. For example, you can set the algorithm to look for “St,” “Cir,” “Blvd,” and other words that suggest an address. You can also use pattern matching to identify potentially sensitive information. For example, a number that takes the form 123-45-6789 is likely to be a Social Security Number.

You can use a free text redaction algorithm to show or hide information by displaying either a “black list” or a “white list.”