Tungsten Replicator is an open source high performance replication engine that works with a number of different source and target databases to provide high-performance and improved replication functionality over the native solution. With MySQL replication, for example, the enhanced functionality and information provided by Tungsten Replicator allows for global transaction IDs, advanced topology support such as multi-master, star, and fan-in, and enhanced latency identification.
In addition to providing enhanced functionality Tungsten Replicator is also capable of heterogeneous replication by enabling the replicated information to be transformed after it has been read from the data server to match the functionality or structure in the target server. This functionality allows for replication between MySQL, Oracle, and Vertica, among others.
Understanding the Tungsten Replicator works requires looking at the overall replicator structure. In the diagram below is the top-level overview of the structure of a replication service.
At this level, there are three major components in the system that provide the core of the replication functionality:
The extractor component reads data from a data server, such as MySQL or Oracle, and writes that information into the Transaction History Log (THL). The role of the extractor is to read the information from a suitable source of change information and write it into the THL in the native or defined format, either as SQL statements or row-based information.
Information is always extracted from a source database and recorded within the THL in the form of a complete transaction. The full transaction information is recorded and logged against a single, unique, transaction ID used internally within the replicator to identify the data.
Appliers within Tungsten Replicator convert the THL information and apply it to a destination data server. The role of the applier is to read the THL information and apply that to the data server.
The applier works with a number of different target databases, and is responsible for writing the information to the database. Because the transactional data in the THL is stored either as SQL statements or row-based information, the applier has the flexibility to reformat the information to match the target data server. Row-based data can be reconstructed to match different database formats, for example, converting row-based information into an Oracle-specific table row, or a MongoDB document.
Transaction History Log (THL)
The THL contains the information extracted from a data server. Information within the THL is divided up by transactions, either implied or explicit, based on the data extracted from the data server. The THL structure, format, and content provides a significant proportion of the functionality and operational flexibility within Tungsten Replicator.
As the THL data is stored additional information, such as the metadata and options in place when the statement or row data was extracted are recorded. Each transaction is also recorded with an incremental global transaction ID. This ID enables individual transactions within the THL to be identified, for example to retrieve their content, or to determine whether different appliers within a replication topology have written a specific transaction to a data server.
These components will be examined in more detail as different aspects of the system are described with respect to the different systems, features, and functionality that each system provides.
From this basic overview and structure of Tungsten Replicator, the replicator allows for a number of different topologies and solutions that replicate information between different services. Straightforward replication topologies, such as master/slave are easy to understand with the basic concepts described above. More complex topologies use the same core components. For example, multi-master topologies make use of the global transaction ID to prevent the same statement or row data being applied to a data server multiple times. Fan-in topologies allow the data from multiple data servers to be combined into one data server.