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DBMS > AllegroGraph vs. Apache IoTDB vs. Google Cloud Datastore vs. Quasardb

System Properties Comparison AllegroGraph vs. Apache IoTDB vs. Google Cloud Datastore vs. Quasardb

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Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonApache IoTDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonQuasardb  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDistributed, high-performance timeseries database
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Time Series DBMSDocument storeTime Series DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.13
Rank#179  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#7  Vector DBMS
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.21
Rank#322  Overall
#29  Time Series DBMS
Websiteallegrograph.comiotdb.apache.orgcloud.google.com/­datastorequasar.ai
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmliotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlcloud.google.com/­datastore/­docsdoc.quasar.ai/­master
DeveloperFranz Inc.Apache Software FoundationGooglequasardb
Initial release2004201820082009
Current release8.0, December 20231.1.0, April 20233.14.1, January 2024
License infoCommercial or Open Sourcecommercial infoLimited community edition freeOpen Source infoApache Version 2.0commercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++
Server operating systemsLinux
OS X
Windows
All OS with a Java VM (>= 1.8)hostedBSD
Linux
OS X
Windows
Data schemeyes infoRDF schemasyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes, details hereyes infointeger and binary
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 indexesyesyesyesyes infowith tags
SQL infoSupport of SQLSPARQL is used as query languageSQL-like query languageSQL-like query language (GQL)SQL-like query language
APIs and other access methodsRESTful HTTP API
SPARQL
JDBC
Native API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
C
C#
C++
Go
Java
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispyesusing Google App Engineno
TriggersyesyesCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodeswith Federationhorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication using PaxosSource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and Sparkyes infousing Google Cloud Dataflowwith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Strong Consistency with Raft
Immediate 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.Immediate Consistency
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes infoTransient mode
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Cryptographically strong user authentication and audit trail
More information provided by the system vendor
AllegroGraphApache IoTDBGoogle Cloud DatastoreQuasardb
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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