Cego implements a relational and transactional database system with support for the SQL query language. The current release contains the most common database features for basic table manipulation and data retrieval. Indexes, foreign keys, views, and stored procedures are also implemented. Future releases (2.0 and above) will support a multi-node database concept with log file shipping for an automatic database application failover.
StreamCruncher is an event processor. It supports a language based on SQL that allows you to define "event processing" constructs like sliding windows, time-based windows, partitions, and aggregates. Such constructs allow for the specification of boundaries (some are time sensitive) on a stream of events that SQL does not provide. Queries can be written using this language, which in turn can be used to monitor streams of incoming events. It also provides a feature similar to materialized views. Joins and sub-queries are also supported to allow event co-relation. A database is used underneath to do the heavy lifting. Pattern matching or multi-stream correlation are also possible.
hamsterdb Embedded Storage is an embedded database engine written in ANSI-C. It includes B+Trees with variable length keys and records. It supports in-memory databases and endian-independent files, database cursors, multiple databases in one file, "record number" databases, and duplicate keys. hamsterdb is very fast and highly configurable. It compiles and runs on Unix platforms, Linux, Microsoft Windows, and Windows CE.
Data stream processing toolkit (dspt) is intended for processing huge amounts (gigabytes) of data in an efficient manner. The structure of the data files is user-defined, and the queries are written in a declarative style. Currently included algorithms range from simple filtering on predicates to aggregation and sorting. It also includes some convenience classes (e.g. for accessing BerkeleyDB databases). The toolkit does not offer as wide a range of operations as an RDBMS, but some measurements of simpler queries have shown it to be more than 10x faster than PostgreSQL.