Uhh... at the risk of being too literal: - Kafka: a service for defining and managing message streams; used in service architectures that communicate by mess

Uhh... at the risk of being too literal: - Kafka: a service for defining and managing message streams; used in service architectures that communicate by message-passing and in high-throughput data processing applications and pipelines. - RabbitMQ: another message queue service; less complex than Kafka. - Kinesis: a message queue service provided by AWS. - Spark: an in-memory distributed computation engine; a central "driver" consumes job definitions, written in code, and farms them out to "workers"; horizontally scalable; a variety of options exist for managed/hosted Spark. - ElasticSearch: a service for indexing data; consumes data blobs and search terms to associate them with; used to build search engines; many convenient utilities for managing search terms and queries. - MapReduce: a paradigm for defining distributed data operations; partitions of a "job" are sent to "mappers" that compute partial results, and those results then flow to "reducers," that combine the partial results into the finished output; Hadoop is the best-known implementation of this paradigm. - BigQuery: a scalable database offered by Google as a service. - InfluxDB: a time series database; used for storing and analyzing data that has a time component. - Hadoop: an implementation of the MapReduce paradigm; many hosted options, or you can run it on your own hardware. - Teradata: a company that sells various data analysis tools that run on its custom data warehouse. - Snowflake: hosted SQL database. - Databricks: hosted Spark.