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DBMS > AgensGraph vs. AllegroGraph vs. Datomic vs. KeyDB

System Properties Comparison AgensGraph vs. AllegroGraph vs. Datomic vs. KeyDB

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Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonAllegroGraph  Xexclude from comparisonDatomic  Xexclude from comparisonKeyDB  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLHigh performance, persistent RDF store with additional support for Graph DBMSDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols
Primary database modelGraph DBMS
Relational DBMS
Document store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Relational DBMSKey-value store
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.20
Rank#321  Overall
#27  Graph DBMS
#143  Relational DBMS
Score1.06
Rank#187  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#7  Vector DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.71
Rank#226  Overall
#33  Key-value stores
Websitebitnine.net/­agensgraphallegrograph.comwww.datomic.comgithub.com/­Snapchat/­KeyDB
keydb.dev
Technical documentationbitnine.net/­documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmldocs.datomic.comdocs.keydb.dev
DeveloperBitnine Global Inc.Franz Inc.CognitectEQ Alpha Technology Ltd.
Initial release2016200420122019
Current release2.1, December 20188.0, December 20231.0.6735, June 2023
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercial infoLimited community edition freecommercial infolimited edition freeOpen Source infoBSD-3
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJava, ClojureC++
Server operating systemsLinux
OS X
Windows
Linux
OS X
Windows
All OS with a Java VMLinux
Data schemedepending on used data modelyes infoRDF schemasyesschema-free
Typing infopredefined data types such as float or dateyesyesyespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nono infobulk load of XML files possiblenono
Secondary indexesyesyesyesyes infoby using the Redis Search module
SQL infoSupport of SQLyesSPARQL is used as query languagenono
APIs and other access methodsCypher Query Language
JDBC
RESTful HTTP API
SPARQL
RESTful HTTP APIProprietary protocol infoRESP - REdis Serialization Protoco
Supported programming languagesC
Java
JavaScript
Python
C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
Clojure
Java
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
Server-side scripts infoStored proceduresyesyes infoJavaScript or Common Lispyes infoTransaction FunctionsLua
TriggersnoyesBy using transaction functionsno
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritancewith Federationnone infoBut extensive use of caching in the application peersSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
none infoBut extensive use of caching in the application peersMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyEventual Consistency
Strong eventual consistency with CRDTs
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDOptimistic locking, atomic execution of commands blocks and scripts
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes infoConfigurable mechanisms for persistency via snapshots and/or operations logs
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes inforecommended only for testing and developmentyes
User concepts infoAccess controlfine grained access rights according to SQL-standardUsers with fine-grained authorization concept, user roles and pluggable authenticationnosimple password-based access control and ACL
More information provided by the system vendor
AgensGraphAllegroGraphDatomicKeyDB
Specific characteristicsKnowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more
Competitive advantagesAllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more
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