- Speakers
Mihai Budiu
- Date
- Description
Modern databases excel at analysis when data changes infrequently. For rapidly changing data, many custom "streaming" or "event processing" systems have been built. To offer near-real time answers, streaming systems compromise on the expressiveness of the computations they perform.
We argue that such compromise is unnecessary. Based on a new theoretical foundation [1] we have built Feldera, a streaming query engine which can execute any traditional database computation in streaming mode, analyzing data as it flows in, and producing near-instantaneous results. The core of our system is an algorithm that converts an arbitrary query on data tables into a query that computes on change streams. The theoretical foundation also gives us a principled way to support new classes of streaming computations, such as mutually recursive queries, or queries that compute on unbounded streams using bounded memory.
We describe the core ideas behind technology and give a demo of our open-source implementation.
[1] DBSP: Automatic Incremental View Maintenance for Rich Query Languages, best paper award at the 2023 conference of Very Large Databases (VLDB)
About Mihai Budiu
Mihai Budiu is chief scientist at Feldera. He has a Ph.D. in CS from Carnegie Mellon University. He was previously employed at VMware Research, Barefoot Networks, and Microsoft Research. Mihai has worked on reconfigurable hardware, computer architecture, compilers, security, distributed systems, big data platforms, large-scale machine learning, programmable networks and P4, data visualization, and databases; four of his papers have received “test of time” awards. He has also received two technology transfer awards.