Explosive growth in DRAM capacities and the emergence of language-integrated query enable a new class of man- aged applications that perform complex query processing on huge volumes of data stored as collections of objects in the memory space of the application. While more flexible in terms of schema design and application development, this approach typically experiences sub-par query execution per- formance when compared to specialized systems like DBMS. To address this issue, we propose self-managed collections, which utilize off-heap memory management and dynamic query compilation to improve the performance of querying managed data through language-integrated query. We eval- uate self-managed collections using both microbenchmarks and enumeration-heavy queries from the TPC-H business intelligence benchmark. Our results show that self-managed collections outperform ordinary managed collections in both query processing and memory management by up to an order of magnitude and even outperform an optimized in- memory columnar database system for the vast majority of queries.