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Here are some ways to handle large volumes of data without exhausting heap memory:

1. Chunking: Break the data into smaller chunks and process them one at a time. This reduces the overall memory needed.

2. Streaming: Process data as it arrives or reads it from disk on-the-fly. This means data is never stored in memory for long periods.

3. Indexing: Use indexes to retrieve specific data so you don't have to load everything into memory.

4. Compressing: Use compression techniques to reduce the amount of memory needed to store the data.

5. Using databases: Use a database to store and manage the data, allowing for efficient querying and retrieval without loading everything into memory at once.

6. Distributed computing: Utilize multiple machines to process the data in parallel, reducing the load on any one machine and allowing for better memory management.

7. Lazy calculation: Delay computation until it’s necessary. You only compute as needed or on-demand ensuring that you are not unnecessarily occupying the memory.