Query processing in the data stream model of computation comes with its own unique challenges.

1. Unbounded Memory Requirements:

   Since data streams are potentially unbounded in size, the amount of storage required to compute an exact answer to a data stream query may also grow without bound. While external memory algorithms for handling data sets larger than main memory have been studied, such algorithms are not well suited to data stream applications since they do not support continuous queries and are typically too slow for real-time response. New data is constantly arriving even as the old data is being processed; the amount of computation time per data element must be low, or else the latency of the computation will be too high and the algorithm will not be able to keep pace with the data stream.

2. Approximate Query Answering:

   When we are limited to a bounded amount of memory it is not always possible to produce exact answers for data stream queries; however, high-quality approximate answers are often acceptable in lieu of exact answers. Sliding Window: One technique for producing an approximate answer to a data stream query is to evaluate the query not over the entire past history of the data streams, but rather only over sliding windows of recent data from the streams. For example, only data from the last week could be considered in producing query answers, with data older than one week being discarded.

3. Blocking Operators:

   A blocking query operator is a query operator that is unable to produce the first tuple of its output until it has seen its entire input. If one thinks about evaluating continuous stream queries using a traditional tree of query operators, where data streams enter at the leaves and final query answers are produced at the root, then the incorporation of blocking operators into the query tree poses problems. Since continuous data streams may be infinite, a blocking operator that has a data stream as one of its inputs will never see its entire input, and therefore it will never be able to produce any output. Doing away with blocking operators altogether would be problematic, but dealing with them effectively is one of the more challenging aspects of data stream computation.

4. Queries Referencing Past Data:

   In the data stream model of computation, once a data element has been streamed by, it cannot be revisited. This limitation means that ad hoc queries that are issued after some data has already been discarded may be impossible to answer accurately. One simple solution to this problem is to stipulate that ad hoc queries are only allowed to reference future data: they are evaluated as though the data streams began at the point when the query was issued, and any past stream elements are ignored (for the purposes of that query). While this solution may not appear very satisfying, it may turn out to be perfectly acceptable for many applications.