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DBMS > AllegroGraph vs. Amazon Neptune vs. Datomic vs. Google Cloud Datastore

System Properties Comparison AllegroGraph vs. Amazon Neptune vs. Datomic vs. Google Cloud Datastore

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Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonAmazon Neptune  Xexclude from comparisonDatomic  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSFast, reliable graph database built for the cloudDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Graph DBMS
RDF store
Relational DBMSDocument store
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.16
Rank#179  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#7  Vector DBMS
Score2.58
Rank#112  Overall
#9  Graph DBMS
#5  RDF stores
Score1.76
Rank#145  Overall
#66  Relational DBMS
Score4.49
Rank#79  Overall
#12  Document stores
Websiteallegrograph.comaws.amazon.com/­neptunewww.datomic.comcloud.google.com/­datastore
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmlaws.amazon.com/­neptune/­developer-resourcesdocs.datomic.comcloud.google.com/­datastore/­docs
DeveloperFranz Inc.AmazonCognitectGoogle
Initial release2004201720122008
Current release8.0, December 20231.0.6735, June 2023
License infoCommercial or Open Sourcecommercial infoLimited community edition freecommercialcommercial infolimited edition freecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, Clojure
Server operating systemsLinux
OS X
Windows
hostedAll OS with a Java VMhosted
Data schemeyes infoRDF schemasschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes, details here
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.no infobulk load of XML files possiblenonono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSPARQL is used as query languagenonoSQL-like query language (GQL)
APIs and other access methodsRESTful HTTP API
SPARQL
OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
RESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Clojure
Java
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispnoyes infoTransaction Functionsusing Google App Engine
TriggersyesnoBy using transaction functionsCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodeswith Federationnonenone infoBut extensive use of caching in the application peersSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.none infoBut extensive use of caching in the application peersMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.
Foreign keys infoReferential integritynoyes infoRelationships in graphsnoyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infowith encyption-at-restyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentno
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)noAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)
More information provided by the system vendor
AllegroGraphAmazon NeptuneDatomicGoogle Cloud Datastore
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
News

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9 February 2024

What is Neuro-Symbolic AI?
23 January 2024

Allegro CL v11 – Now Available! – The Neuro-Symbolic AI Programming Platform
8 January 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
AllegroGraphAmazon NeptuneDatomicGoogle Cloud Datastore
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