There are two main types of schemes: one-time projects and ongoing processes. Replicating data usually falls into the latter category, necessitating frequent data copying to ensure updates from one source are propagated across the entire system.
The three primary techniques for replication are full, incremental, and log-based replication. Each method has its own set of pros and cons, and the key challenge lies in striking a balance between data consistency and system performance. Selecting the appropriate approach will largely depend on your intended use for the replicated data, the data volume, and the storage method employed.
1. Full-table replication involves the complete duplication of all existing, new, and updated data from the primary data repository to the target, and in some cases, to each site within your distributed system.
Pros: The technique offers several benefits. First, it ensures higher data availability as a replicated database guarantees data redundancy even if one of the sites fails. Second, it enables faster queries due to localized processing. Additionally, if key-based replication is not viable in the primary database or if data records are frequently hard deleted, employing a full-table is a suitable alternative.
Cons: Full-table database replication comes with certain drawbacks. Primarily, it can lead to increased network bandwidth loads and require additional processing power, resulting in higher costs. Moreover, achieving concurrency becomes more challenging, and the update process slows down significantly, as each individual update must be executed across all sites in the distributed system.
2. Key-based incremental replication relies on a specific replication key column in the primary data repository to identify updated and new data. It selectively updates data in the replica databases that have changed since the last update. Commonly, this key is represented by a timestamp, datestamp, or an integer.
Pros: Key-based replication provides heightened efficiency as only the modified data rows are copied during each update.
Cons: Key-based replication cannot detect and replicate data that has been hard-deleted in the source. This is because when a record is deleted in the primary database, the corresponding key value is also deleted.
3. Log-based incremental replication operates by copying data according to the content of the database's binary log file. This log file contains crucial details about alterations in the primary database, including inserts, updates, and deletes. The majority of database vendors offer support for this method, with notable examples being MySQL, PostgreSQL, Oracle, and MongoDB.