A database value as of a point in time. With asOf, you can reuse existing queries and rules to ask questions about points in time other than the present.
Something that can be said about an entity. An
attribute has a name, e.g.
:firstName, and a value type, e.g.
:db.type/long, and a cardinality.
The database t that is the basis for the current database, i.e. the most recent point-in-time that this database has seen.
a server that provides access to private network from an external network, rather than allowing direct access to that internal network
Property of an attribute that specifies how many
values of the attribute can be associated with a single reference entity.
Possible values are
Nodes use a multi-layered cache that consists of an object Cache, valcache, and an EFS Cache.
Assumption that truth is what the database knows. Databases that intend to store data of record typically make the closed world assumption. Datomic adheres to the closed world model.
An Auto Scaling Group of compute resources, either a primary compute group or a query group.
Client object that provides access to a database. Programs can use a connection to submit transactions and queries.
Datomic uses a consistent hash ring to route transactions to a preferred Node per database. This is a performance optimization only: any Primary Compute Node can handle any transaction.
A covering index contains (rather than points to) the data. Datomic indexes are covering indexes.
An atomic fact in a database, composed of entity/attribute/value/transaction/added. Pronounced like "datum", but pluralizes as datoms.
A deductive query system, typically consisting of:
- A database of facts
- A set of rules for deriving new facts from existing facts
- a query processor that, given some partial specification of a
fact or rule: finds all instances of that specification implied by the database and rules, i.e. all the matching facts
Datomic's built-in query is an implementation of Datalog.
The extensbible data notation is used by Datomic and other applications as a data transfer format.
A cache of segments in EFS that will typically contains the entirety of all databased, eliminating the need to read from S3.
an operation that guarantees the existence and correct configuration of a resource. Ensure is typically built out of AWS primitives that create, query, and update resources.
The first component of a datom, specifying who or what the datom is about. Also the collection of datoms associated with a single entity, as in the Java type, Entity.
An opaque identifier assigned by Datomic that uniquely identifies an entity. Entity ids are integers for efficiency, but application programs should treat them as opaque ids.
a value that identifies an entity. Can be an entity id, an ident, or a lookup ref.
an instantiated set of all the resources need to run an application.
a unique identifier external to Datomic. Typical
external key types are email address, UUID, and URI. External key
attributes should be declared as
Period of time bounded by writing index to storage. During an epoch, indexing is done in memory. At epoch boundaries, the in-memory index is merged with the persistent index, and a new persistent index is written to the storage service (without blocking the system).
Fressian is an extensible binary format that is used everywhere data is serialized by Datomic: on the wire, at rest, and in caches. Fressian is designed to be:
- simple to implement and consume
- compact and fast
- friendly to dynamic and static languages
- compressible in domain-specific ways
A value of type
:db/ident that uniquely identifies an entity.
Your application code, running on Datomic compute nodes.
Prefix portion of a keyword used to make the keyword globally unique. Namespaces serve a similar function to table names in a relational store, without imposing any obligations or limitations, e.g. an entity can have attributes from more than one namespace.
named slots for application configuration data.
a CloudFormation stack providing computational resources. Every Datomic system has a single primary compute stack, and may also have multiple query groups.
a declarative way to make hierarchical selections of information about entities
An AutoScaling Group (ASG) of nodes used to dedicate bandwidth, processing power, and caching to particular jobs. Unlike sharding, query groups never dictate who a client must talk to in order to store or retrieve information. Any node in any group can handle any request.
An attribute that refers to another entity. References
always have the value type
A named group of query constraints, to allow re-use of logic across queries.
The durable elements managed by a Datomic system.
A complete Datomic installation, consisting of storage resources, a primary compute stack, and optional query groups.
The set of possible attributes that can be associated with entities. Any entity can have any attribute.
a built-in attribute used to define schema,
e.g. all attributes are named by
Indexes store datoms as a tree of segments, where the leaf nodes contain a few thousand datoms each.
Subsystem responsible for persistence. Datomic Cloud uses DynamoDB as its storage service.
Data structure that can be resolved to a point in time in a database. Can be a database t, a tx, or a date.
A point in time in a database. Every transaction is assigned a numeric t value greater than any previous t in the database, and all processes see a consistent succession of ts.
An entity representing a transaction. Every datom in a Datomic database includes the tx that created it, allowing recovery of the entire history of the database. Transactions are automatically associated with wall-clock time, but are otherwise ordinary entities. In particular, application code can make additional assertions about transactions.
An atomic unit of work in a database. All Datomic writes are transactional, fully serialized, and ACID (Atomic, Consistent, Isolated, and Durable).
a function that runs inside a transaction, taking the current database value plus user arguments and expanding into data to be added by the transaction.
Either insert or update an entity, depending on whether the unique entity already exists.
An SSD-backed cache of segments. Valcache is similar in performance to memcached but durable and capacious.