Nowadays, every business application is using caching to improve data retrieval performance and reduce the need to get data directly from the database. Since databases started to slow down modern web applications, a variety of data caching techniques have been proposed. Data caching helps address the issue of database scalability and performance, but it also creates another issue with data inconsistency maintenance.
Data inconsistency issues occur when the application that is interacting with the database has other applications modifying it. Then your application is not responsible for updating the database in all scenarios, so the cache is not synchronized. If there is no other application interacting with the database other than your application, then the chances of data becoming stale are very less, as all the changes are simultaneously synchronized between the cache and the database.
The validity of data in the network is called cache consistency. Cache consistency makes sure that only valid data is returned in response to a generated query and that all stale data is immediately removed from the cache. So, here I will discuss the powerful mechanisms that NCache provides its users so they never have to worry about maintaining data consistency between a cache and the database.
Cache-database synchronization
Cache inconsistencies can occasionally be as bad for a database as data loss. If the data in the cache is not updated, then the application that is depending on the cache to make decisions suffers as both the data used and the decision made become invalid. Caches are frequently used to scale read-intensive workloads. As a result, an unsynchronized cache and database can create a major impact on the decision-making based on the provided data and data accuracy will also be affected which will in turn cause a business loss.
Reasons & Consequences of data inconsistency
If a cache contains static data means no changes occur and data inconsistency doesn’t take place (using read operations e.g. get). But if the data is frequently changing (using write operations e.g. add, update, insert, delete) then with each data change, the cache has to synchronize itself concerning the primary data source. Understanding the unique challenges of data inconsistency is particularly challenging and the most common reasons for data inconsistency are:
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Data is changed in the database but not reflected in the cache
Upon each write operation, the data in the primary database changes, but the change in the database is not reflected in the cache. The application that uses data from the cache then gets stale data which creates a huge performance impact on mission-critical applications.
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Data is changed in the cache but not reflected in the database
Data inconsistency issues can also occur due to changes not being reflected in the database in case of data change in the cache and the application serving directly from the database will have stale data.
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Delay in updating the cache
There lies a possibility that data inconsistency issues can occur due to delays in reflecting the changes.
For instance, the same object might have a different copy in the cache and database in case of a delay in updating the cache causing data inconsistency. The read path appears to follow the standard procedure, but there should also be a mechanism for the write path to synchronize data, whenever a change in the database occurs, to keep the cache and database synchronized.
Keep your data consistent using NCache
NCache is aware of the value of data consistency for mission-critical applications as well as applications supporting high user loads. NCache provides many powerful features with extensive properties to keep data consistent in the cache concerning the database and vice versa. In case of any data change in the database, the cache holding the data becomes stale and inconsistent which impacts data accuracy and the business negatively – leading to a loss. So, keeping in mind these issues, NCache gives:
1. Data Expiration in Cache
NCache’s Data Expiration feature is a lifesaver for many critical business applications that need fresh data at all times and get rid of stale data which is no longer needed in the cache.
Expiring stale data from the cache results in relevant and updated data being provided to the client. Data Expiration in NCache has two further types that are absolute and sliding. Absolute expiration is used with the data that is to be used for a specific time and after that, it is no longer required. So instead of having idle data in the cache, it expires after the specified period. Read this blog to learn how to keep data fresh in the cache using Expiration in NCache.
Figure 1 Absolute Expiration in NCache
NCache Details Data Expiration in NCache Absolute Expiration
However, sliding expiration has a specified expiration time but depends on usage. As the time is reset every time it is accessed irrespective of how much time passed previously. Such data is added to the cache within the specified time which slides further in case it is used again in the given time.
Figure 2 Sliding Expiration in NCache
NCache Details Data Expiration in NCache Sliding Expiration
2. Cache Refresher
NCache gives a Cache Refresher feature to refresh data in the cache after a specific time interval. Cache refresher works in an optimized fashion. The cache refresher updates specified datasets at user-provided intervals to prevent data from going stale. To check which data sets need updating/refreshing, a thread runs after a specific time, known as the refresh interval. Users can configure the refresh interval through the NCache Manager or the NCache PowerShell cmdlets. Read the blog here, for more information on how to keep your data fresh in the cache using Cache Refresher.
Figure 3 Working of Cache Refresher in NCache
3. Cache Dependencies
To improve application performance and scalability, the majority of applications that frequently make database calls now employ distributed caching. For this reason, you would prefer that cache data be invalidated and deleted whenever any database data changes take place.
NCache offers a mechanism for invalidating data – Cache dependencies.
Cache dependencies are yet another far-reaching feature with great usage. Cache dependencies work promptly, and as soon as the change in the database occurs, the object from the cache is automatically removed. Data from the database is fetched again and the cache always contains updated data. Data in the cache can have dependency-based relations with items, a file on some location, a record in a database, results of a particular query, or another cached item, such that any change in the item can invalidate the data in the cache. Read more about managing relationships in the cache using data dependencies, here.
NCache Details Managing Relational Data Data Dependency Docs
4. Data source Providers
Caching is primarily used to cache data to maximize performance. Client applications may need to perform operations on the data source while using the cache. NCache provides Read-Through and Write-Through/Write-Behind caching to enable transparent read/write operations on the data source. Using this feature, the client applications can read or write data to the data source through the cache, if needed.
- ReadThru
NCache communicates with the data source using your unique Read-Through provider. In Read-Through Caching, in the event of a cache miss, NCache will contact your provider to load data behind the get call. The Read-Through provider will be active (initialized) on all cache server nodes in clustered caches with multiple servers, but Read-Through operations will be carried out by the node that receives the get operation by the topology.
- WriteThru
When using Write-Through caching, an operation is first applied to the cache store and then the configured data source is synchronously updated.
Operations using Write-Through will be finished after NCache performs such operations on the data source. If immediate data source updates are necessary and you must update the data source as soon as the cache is updated, you can use write-through caching. Read the following blog for more information on WriteThru.
Figure 4 Update Application data (Write-Through)
- WriteBehind
Data source operations in Write-Behind are carried out asynchronously following NCache operations on the cache-store. These operations are queued up after updating the cache store and then asynchronously applied to configured data sources. As a result, using Write-Behind will speed up cache operations.
Conclusion
Maintaining data consistency between the cache and database is made easy by NCache’s powerful syncing mechanisms that work synchronously and asynchronously to always provide updated data to mission-critical applications. By not compromising on data accuracy and ensuring high availability of data, NCache is giving its users a seamless way to synchronize data. So, use NCache to remove performance bottlenecks related to your data storage and databases. As NCache automatically eliminates the risk of data inconsistencies between cache and data source to help you avoid business losses due to data inconsistencies.
