updated with a single pass over streaming tuples in their arrival order • Small space: memory footprint poly-logarithmic in the stream size • Low time: fast update and query times • Delete-proof: University 2020 Issues with synopses • They are lossy compressions of streams • trade-off memory footprint for accuracy • Query results are approximate with either deterministic or probabilistic error

Machine Learning (ML) pipelines and ETL processes. If you’re already familiar with Python and libraries such as Pandas, then PyFlink makes it simpler to leverage the full capabilities of the Flink ecosystem

Machine Learning (ML) pipelines and ETL processes. If you’re already familiar with Python and libraries such as Pandas, then PyFlink makes it simpler to leverage the full capabilities of the Flink ecosystem