You should be talking about the mainstream frameworks in the big data platform, I list:

(a) Hadoop ecosystem

HDFS: Distributed file system, to solve the storage of big data

Yarn (MapReduce): Distributed computing framework, to solve the computation of big data

Hive: Data analytics engine in Hadoop with SQL support

HBase: HDFS-based NoSQL database

ZooKeeper: Distributed orchestration service that can be used to implement HA (High Availability Architecture)

Others

(ii) Spark ecosystem

Spark Core: the core of Spark, used for offline computing

Spark SQL: Spark's data analytics engine, supporting SQL statements

Spark Streaming: Spark's streaming computation engine, but still essentially offline computation

MLlib: a machine learning framework

(iii) Flink ecosystem

Flink DataSet: Flink batch processing (offline computing) API

Flink DataStream: Flink streaming processing (real-time computing) API

Flink Table&SQL: Flink's data analytics engine, supporting SQL statements

MLlib: a machine learning framework