Developing high-performance software is a difficult task that requires the use of low-level, architecture-specific programming models (e.g., OpenMP for CMPs, CUDA for GPUs, MPI for clusters). It is typically not possible to write a single application that can run efficiently in different environments, leading to multiple versions and increased complexity. Domain-Specific Languages (DSLs) are a promising avenue to enable programmers to use high-level abstractions and still achieve good performance on a variety of hardware. This is possible because DSLs have higher-level semantics and restrictions than general-purpose languages, so DSL compilers can perform higher-level optimization and translation. However, the cost of developing performance-oriented DSLs is a substantial roadblock to their development and adoption. In this article, we present an overview of the Delite compiler framework and the DSLs that have been developed with it. Delite simplifies the process of DSL development by providing common components, like parallel patterns, optimizations, and code generators, that can be reused in DSL implementations. Delite DSLs are embedded in Scala, a general-purpose programming language, but use metaprogramming to construct an Intermediate Representation (IR) of user programs and compile to multiple languages (including C++, CUDA, and OpenCL). DSL programs are automatically parallelized and different parts of the application can run simultaneously on CPUs and GPUs. We present Delite DSLs for machine learning, data querying, graph analysis, and scientific computing and show that they all achieve performance competitive to or exceeding C++ code.