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

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

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Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonAmazon Neptune  Xexclude from comparisonBrytlyt  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 cloudScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLAutomatically 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
Score1.06
Rank#187  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#7  Vector DBMS
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score0.29
Rank#288  Overall
#131  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Websiteallegrograph.comaws.amazon.com/­neptunebrytlyt.iocloud.google.com/­datastore
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmlaws.amazon.com/­neptune/­developer-resourcesdocs.brytlyt.iocloud.google.com/­datastore/­docs
DeveloperFranz Inc.AmazonBrytlytGoogle
Initial release2004201720162008
Current release8.0, December 20235.0, August 2023
License infoCommercial or Open Sourcecommercial infoLimited community edition freecommercialcommercialcommercial
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 languageC, C++ and CUDA
Server operating systemsLinux
OS X
Windows
hostedLinux
OS X
Windows
hosted
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 possiblenoyes infospecific XML-type available, but no XML query functionality.no
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSPARQL is used as query languagenoyesSQL-like query language (GQL)
APIs and other access methodsRESTful HTTP API
SPARQL
OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (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
.Net
C
C++
Delphi
Java
Perl
Python
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispnouser defined functions infoin PL/pgSQLusing Google App Engine
TriggersyesnoyesCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodeswith FederationnoneSharding
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.Source-replica replicationMulti-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 graphsyesyes 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-restyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
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)fine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)
More information provided by the system vendor
AllegroGraphAmazon NeptuneBrytlytGoogle 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
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