Dealing with data in microservice architectures - part 3 - Replication

This page summarizes the projects mentioned and recommended in the original post on dev.to

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  • PostgreSQL

    Mirror of the official PostgreSQL GIT repository. Note that this is just a *mirror* - we don't work with pull requests on github. To contribute, please see https://wiki.postgresql.org/wiki/Submitting_a_Patch

  • We hook into our source database for example with Kafka Connect and Debezium. Debezium reads the database’s transaction log (TX Log). Debezium forwards changes to the transaction log to Kafka topics. The microservices (MS) consume the data from the topics and fill their databases (DB) as needed. We can optimize the microservice-databases for the respective use case. For example, one microservice might need a PostgreSQL whereas another needs a Redis.

  • MongoDB

    The MongoDB Database

  • In our example, some machine learning tool-set (ML-Magic) analyses the raw data. The result of the analysis is a categorization of the financial transaction. The ML-Magic combines the analysis and the financial transaction data. Finally, the ML-Magic stores this result in a separate enhanced business database. In the example, this is a MongoDB database.

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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  • Redis

    Redis is an in-memory database that persists on disk. The data model is key-value, but many different kind of values are supported: Strings, Lists, Sets, Sorted Sets, Hashes, Streams, HyperLogLogs, Bitmaps.

  • We hook into our source database for example with Kafka Connect and Debezium. Debezium reads the database’s transaction log (TX Log). Debezium forwards changes to the transaction log to Kafka topics. The microservices (MS) consume the data from the topics and fill their databases (DB) as needed. We can optimize the microservice-databases for the respective use case. For example, one microservice might need a PostgreSQL whereas another needs a Redis.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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