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connectors/cassandra/README.md

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# redis-connect-cassandra
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redis-connect-cassandra is a connector framework for capturing row level changes (INSERT, UPDATE and DELETE) from Cassandra nodes (source) and writing them to a Redis Enterprise database (Target).
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The first time the connector connects to a Cassandra node, it performs a snapshot of all CDC-enabled tables in all key spaces. The connector will also read the changes that are written to Cassandra commit logs and generates corresponding insert, update, and delete events. All events for each table are recorded in a separate Redis data structure, where they can be consumed easily by applications and services.
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The first time the connector connects to a Cassandra node, it performs a snapshot of all CDC-enabled tables in all key spaces. The connector will also read the changes that are written to Cassandra commit logs and generates corresponding insert, update, and delete events. All events for each table are recorded in a separate [Redis data structure or module](../../docs/writers.md) of your choice, where they can be consumed easily by applications and services.
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## Overview
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connectors/gemfire/README.md

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The connector is also tolerant of failures. As the connector reads changes and produces events, it records the Checkpoint i.e. <i>DURABLE_CLIENT_ID</i> in the target Redis Enterprise database that is associated with _CDC_ record with each event.
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If the connector stops for any reason (including communication failures, network problems, or crashes), upon restart it simply continues reading the Regions where it last left off.
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The connector then produces a _change event_ for every row-level insert, update, and delete operation that was published via the _CDC API_, while recording all the change events for each table in a Redis Enterprise Database with a choice of your data structure such as [Hashes](https://redis.io/topics/data-types#hashes). Please see a list of supported data structures [here](../../docs/writers.md), and it's usage examples.
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## Architecture
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connectors/mssql/README.md

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redis-connect-sqlserver is a Redis Connect connector for capturing changes (INSERT, UPDATE and DELETE) from MS SQL Server (source) and writing them to a Redis Enterprise database (Target). redis-connect-sqlserver cdc connector implementation is based on <a href="https://debezium.io/documentation/reference/stable/connectors/postgresql.html" target="_blank">Debezium</a>, which is an open source distributed platform for change data capture.
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The first time redis-connect-sqlserver connects to a SQL Server database/cluster, it reads a consistent snapshot of all the schemas.
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When that snapshot is complete, the connector continuously streams the changes that were committed to SQL Server and generates a corresponding insert, update or delete event.
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All the events for each table(s) are recorded in a separate Redis data structure or module of your choice, where they can be easily consumed by applications and services.
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All the events for each table(s) are recorded in a separate [Redis data structure or module](../../docs/writers.md) of your choice, where they can be easily consumed by applications and services.
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## Overview
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The functionality of the connector is based upon [change data capture](https://docs.microsoft.com/en-us/sql/relational-databases/track-changes/about-change-data-capture-sql-server?view=sql-server-2017) feature provided by SQL Server Standard since [SQL Server 2016 SP1](https://blogs.msdn.microsoft.com/sqlreleaseservices/sql-server-2016-service-pack-1-sp1-released/) or Enterprise edition.
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Using this mechanism, a SQL Server capture process monitors all databases and tables the user is interested in and stores the changes into specifically created _CDC_ tables that have a stored procedure facade.
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The database operator must [enable](https://docs.microsoft.com/en-us/sql/relational-databases/track-changes/enable-and-disable-change-data-capture-sql-server?view=sql-server-2017) _CDC_ for the table(s) that should be captured by the connector.
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The connector then produces a _change event_ for every row-level insert, update, and delete operation that was published via the _CDC API_, while recording all the change events for each table in a Redis Enterprise Database with a choice of your data structure such as [Hashes](https://redis.io/topics/data-types#hashes).
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The connector then produces a _change event_ for every row-level insert, update, and delete operation that was published via the _CDC API_, while recording all the change events for each table in a Redis Enterprise Database with a choice of your data structure such as [Hashes](https://redis.io/topics/data-types#hashes). Please see a list of supported data structures [here](../../docs/writers.md), and it's usage examples.
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The connector is also tolerant of failures.
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As the connector reads changes and produces events, it records the position i.e. [(_LSN / Log Sequence Number_)](https://docs.microsoft.com/en-us/sql/relational-databases/sql-server-transaction-log-architecture-and-management-guide?view=sql-server-ver15#Logical_Arch) in the target Redis Enterprise database that is associated with _CDC_ record with each event.

connectors/mysql/README.md

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redis-connect-mysql is a Redis Connect connector for capturing changes (INSERT, UPDATE and DELETE) from MySQL (source) and writing them to a Redis Enterprise database (Target). redis-connect-mysql cdc connector implementation is based on <a href="https://debezium.io/documentation/reference/stable/connectors/mysql.html" target="_blank">Debezium</a>, which is an open source distributed platform for change data capture.
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The first time redis-connect-mysql connects to a MySQL database, it reads a consistent snapshot of all the schemas.
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When that snapshot is complete, the connector continuously streams the changes that were committed to MySQL and generates a corresponding insert, update or delete event.
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All the events for each table(s) are recorded in a separate Redis data structure or module of your choice, where they can be easily consumed by applications and services.
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All the events for each table(s) are recorded in a separate [Redis data structure or module](../../docs/writers.md) of your choice, where they can be easily consumed by applications and services.
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## Architecture
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connectors/oracle/README.md

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redis-connect-oracle is a Redis Connect connector for capturing changes (INSERT, UPDATE and DELETE) from Oracle (source) and writing them to a Redis Enterprise database (Target). redis-connect-oracle cdc connector implementation is based on <a href="https://debezium.io/documentation/reference/stable/connectors/oracle.html" target="_blank">Debezium</a>, which is an open source distributed platform for change data capture.
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The first time redis-connect-oracle connects to an Oracle database, it reads a consistent snapshot of all the schemas.
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When that snapshot is complete, the connector continuously streams the changes that were committed to Oracle and generates a corresponding insert, update or delete event.
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All the events for each table(s) are recorded in a separate Redis data structure or module of your choice, where they can be easily consumed by applications and services.
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All the events for each table(s) are recorded in a separate [Redis data structure or module](../../docs/writers.md) of your choice, where they can be easily consumed by applications and services.
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## Architecture
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### Sample JobConfig.yml under redis-connect-oracle/config/samples/oracle folder
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You can have one or more JobConfig.yml (or with any name e.g. JobConfig-<table_name>.yml) and specify them in the Setup.yml under jobConfig: tag. If specifying more than one table (as below) then make sure maxNumberOfJobs: tag under JobManager.yml is set accordingly e.g. if maxNumberOfJobs: tag is set to 2 then Redis Connect will start 2 cdc jobs under the same JVM instance. If the workload is more and you want to spread out (scale) the cdc jobs then create multiple JobConfig's and specify them in the Setup.yml under jobConfig: tag.
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You can have one or more JobConfig.yml (or with any name e.g. JobConfig-<table_name>.yml) and specify them in the Setup.yml under jobConfig: tag. If specifying more than one table (as below) then make sure maxNumberOfJobs: tag under JobManager.yml is set accordingly e.g. if maxNumberOfJobs: tag is set to 2 then Redis Connect will start 2 cdc jobs under the same JVM instance. If the workload is more, and you want to spread out (scale) the cdc jobs then create multiple JobConfig's and specify them in the Setup.yml under jobConfig: tag.
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```yml
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jobId: ${jobId}

connectors/postgres/README.md

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redis-connect-postgres is a Redis Connect connector for capturing changes (INSERT, UPDATE and DELETE) from PostgreSQL (source) and writing them to a Redis Enterprise database (Target). redis-connect-postgres cdc connector implementation is based on <a href="https://debezium.io/documentation/reference/stable/connectors/postgresql.html" target="_blank">Debezium</a>, which is an open source distributed platform for change data capture.
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The first time redis-connect-postgres connects to a PostgreSQL database, it reads a consistent snapshot of all the schemas.
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When that snapshot is complete, the connector continuously streams the changes that were committed to PostgreSQL and generates a corresponding insert, update or delete event.
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All the events for each table(s) are recorded in a separate Redis data structure or module of your choice, where they can be easily consumed by applications and services.
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All the events for each table(s) are recorded in a separate [Redis data structure or module](../../docs/writers.md) of your choice, where they can be easily consumed by applications and services.
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## Architecture
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