Bioinformatic pipelines have become an essential tool set for analyzing large amounts of biological data. A pipeline typically includes a multitude of data processing steps, possibly comprising numerous tools orchestrated by the pipeline. There have been several studies comparing different methods and tools within the pipeline, often using mock data or data oriented towards human medicine, and mostly 16S data. However, there is a lack of comparisons using environmental data and using 18S data. The aim of this study is to compare bioinformatics pipelines for analysis of 16S and 18S rRNA amplicon sequence data, considering taxonomic classification and in environmental variation in shallow inshore habitats specifically. In this context, it is important to understand both spatial and temporal variations, as well as both abundance and specific organisms. We compared five different pipelines in this study and concluded that a recommendation should be to run at least two of these pipelines when analyzing data to validate that results are consistent. Also, the choice of a reference database for taxonomy classification is an important consideration to include as well. Our recommendation is to pick two of Ampliseq, QIIME2-DADA2, and QIIME2-Deblur pipelines for 16S data. For 18S data, it should be DADA2-based pipelines which can use the PR2 reference database.