Datomic

Key Features

* Separating reads and writes - When reads are separated from writes, writes are never held up by queries. In the Datomic architecture, the transactor is dedicated to transactions, and need not service reads at all! * Integrated data distribution - Each peer and transactor manages its own local cache of data segments, in memory. This cache self-tunes to the working set of that application. * Every peer gets its own brain (query engine and cache) - Moving a proper, index-supported, declarative query engine into applications will enable them to work with data at a higher level than ever before, and at application-memory speeds. * Elasticity - Application servers are frequently scaled up and down as demand fluctuates, but traditional databases, even with read-replication configured, have difficulty scaling query capability similarly. Putting query engines in peers makes query capability as elastic as the applications themselves. In addition, putting query engines into the applications themselves means they never wait on each other's queries. * Ready for the cloud - All components are designed to run on commodity servers, with expectations that they, and their attached storage, are ephemeral. * The speed of memory - While the (disk-backed) storage service constitutes the data of record, the rest of the system operates primarily in memory. Since memory prices are falling faster than business information is growing, it is only a matter of time before most businesses' data will fit in memory.