Datomic

Datomic is a proprietary database management system. It is an operational DBMS, in other words, it allows updates in real time. Instead of assigning and overwriting values into named attributes, Datomic keeps track of all immutable facts over time, which sets Datomic apart because previous states can be accessed easily. Datomic is also a distributional DBMS, which provides horizontal read scalability. Therefore, Datomic is a good fit for storing a history of valuable records that requires operational flexibility and read scalability. In addition, Datomic Cloud is built for AWS integration and is a quicker and easier way to access Datomic on AWS.

History

Early March 2012, the Relevance team (later joined with Metadata to form Cognitect) around Rich Hickey released Datomic, which they have started to work on since 2010.

Query Interface

Datalog

Datomic's query interface is an extension from Datalog. The main difference is that Datalog systems usually have a global fact database and a set of rules, but Datomic Datalog could take multiple databases and sets of rules.

Storage Model

Custom

Datomic treats storage as a service, which means that Datomic only provides the ways to access underlying storage, but doesn't provide the actual storage.

Isolation Levels

Serializable

There is only one thread responsible for writing transactions, so transactions are always serializable.

Stored Procedures

Supported

Stored procedures are represented as "transaction functions" in Datomic.

Indexes

B+Tree

Datomic indexes are covering indexes. In other words, instead of storing reference to data in the index, Datomic directly reads data from index.

Storage Architecture

Hybrid

Foreign Keys

Supported

Data Model

Relational Key/Value Entity-Attribute-Value

Datomic stores immutable facts as datoms over time. A datom follows the form of `(entity, attribute, value, time).`

System Architecture

Shared-Nothing

Each "peer" in Datomic that communicates with storage services and transactors has its own cache.

Compression

Naïve (Record-Level)

Index trees contain "segments," arrays of datoms that are serialized and then compressed with zip. Compression allows more efficient caching and storage.

Datomic Logo
Website

https://www.datomic.com/

Tech Docs

https://docs.datomic.com/

Developer

Cognitect, Inc.

Country of Origin

US

Start Year

2012

Project Type

Commercial

Written in

Clojure, Java

Supported languages

Clojure, Java

Compatible With

Cassandra, CouchDB, DynamoDB, Infinispan, MySQL, Oracle NoSQL, Oracle RDBMS, PostgreSQL, Riak

Operating Systems

All OS with Java VM, Hosted

Licenses

Proprietary

Wikipedia

https://en.wikipedia.org/wiki/Datomic