Bowtie2 is no longer the fastest aligner. As you point out, BWA is faster, despite being based on the same Burrows-Wheeler transform as Bowtie2. As @user172818 points out, bwa-aln will work better for very short sequences under 36bp.
For transcript mapping, Salmon and Kallisto are much faster, but have been designed to optimise cDNA-seq mapping. Their speed is gained from avoiding a strict base-to-base alignment, but they can output mostly-aligned reads (i.e. position-only, without local alignment) as pseudo-alignments. See here for more details.
Both Kallisto and Salmon can do additional bootstrapping that is interpreted by sleuth (and other downstream tools) for improved performance in isoform detection. They can also output counts that are equivalent to read-level counts from other programs, which can then be used by other downstream gene-based differential expression analysis software (e.g. DESeq2). Salmon has additional options that can correct mappings for sequence-level and GC bias.
HISAT2 is from the same group as Bowtie2, and does the same sort of stuff, but with a few optimisations added on top. In particular, it's much better at working out split reads from RNASeq runs, while also working for genomic alignments. Like Bowtie2, it will do local alignment of reads.
For quick genomic alignment of long reads, minimap2 works well. For high-accuracy alignment (but comparatively slower), LAST works well.
There are two programs I have used that are specifically designed for long read transcript quantification that process minimap2 read mapping into isoform counts (based on a provided reference transcriptome): bambu and oarfish. Both seem to work reasonably well; bambu is a native R package with nice isoform visualisation included; oarfish produces Salmon-like output that can be imported into R via tximport.
Most bioinformaticians seem to prefer STAR for things that Bowtie2 was previously used for. I'm not yet convinced it's a better alternative, and currently prefer HISAT2 for high accuracy short-read alignment.
According to @kasper-thystrup-karstensen, STAR is able to read Chimeric alignments (for detecting e.g. circular RNA through custom coding).
