This topic explains data storage and distribution options in VMware Tanzu GemFire.
Tanzu GemFire provides several models for data storage and distribution, including partitioned or replicated regions as well as distributed or non-distributed regions (local cache storage).
Peer-to-Peer Region Storage and Distribution
At its most general, data management means having current data available when and where your applications need it. In a properly configured Tanzu GemFire installation, you store your data in your local members and Tanzu GemFire automatically distributes it to the other members that need it according to your cache configuration settings. You may be storing very large data objects that require special consideration, or you may have a high volume of data requiring careful configuration to safeguard your application’s performance or memory use. You may need to be able to explicitly lock some data during particular operations. Most data management features are available as configuration options, which you can specify either using the gfsh cluster configuration service, cache.xml file or the API. Once configured, Tanzu GemFire manages the data automatically. For example, this is how you manage data distribution, disk storage, data expiration activities, and data partitioning. A few features are managed at run-time through the API.
At the architectural level, data distribution runs between peers in a single cluster and between clients and servers.
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Peer-to-peer provides the core distribution and storage models, which are specified as attributes on the data regions.
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For client/server, you choose which data regions to share between the client and server tiers. Then, within each region, you can fine-tune the data that the server automatically sends to the client by subscribing to subsets.
Data storage in any type of installation is based on the peer-to-peer configuration for each individual cluster. Data and event distribution is based on a combination of the peer-to-peer and system-to-system configurations.
Storage and distribution models are configured through cache and region attributes. The main choices are partitioned, replicated, or just distributed. All server regions must be partitioned or replicated. Each region’s data-policy and subscription-attributes, and its scope if it is not a partitioned region, interact for finer control of data distribution.
Storing Data in the Local Cache
To store data in your local cache, use a region refid with a RegionShortcut or ClientRegionShortcut that has local state. These automatically set the region data-policy to a non-empty policy. Regions without storage can send and receive event distributions without storing anything in your application heap. With the other settings, all entry operations received are stored locally.
