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DBMS > AnzoGraph DB vs. Apache IoTDB vs. GigaSpaces vs. SiriDB vs. Yaacomo

System Properties Comparison AnzoGraph DB vs. Apache IoTDB vs. GigaSpaces vs. SiriDB vs. Yaacomo

Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonApache IoTDB  Xexclude from comparisonGigaSpaces  Xexclude from comparisonSiriDB  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsOpen Source Time Series DBMSOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelGraph DBMS
RDF store
Time Series DBMSDocument store
Object oriented DBMS infoValues are user defined objects
Time Series DBMSRelational DBMS
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#303  Overall
#25  Graph DBMS
#14  RDF stores
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score1.03
Rank#188  Overall
#32  Document stores
#6  Object oriented DBMS
Score0.07
Rank#378  Overall
#42  Time Series DBMS
Websitecambridgesemantics.com/­anzographiotdb.apache.orgwww.gigaspaces.comsiridb.comyaacomo.com
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.gigaspaces.com/­latest/­landing.htmldocs.siridb.com
DeveloperCambridge SemanticsApache Software FoundationGigaspaces TechnologiesCesbitQ2WEB GmbH
Initial release20182018200020172009
Current release2.3, January 20211.1.0, April 202315.5, September 2020
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoApache Version 2.0Open Source infoApache Version 2; Commercial licenses availableOpen Source infoMIT Licensecommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, C++, .NetC
Server operating systemsLinuxAll OS with a Java VM (>= 1.8)Linux
macOS
Solaris
Windows
LinuxAndroid
Linux
Windows
Data schemeSchema-free and OWL/RDFS-schema supportyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes infoNumeric datayes
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.nonono infoXML can be used for describing objects metadatanono
Secondary indexesnoyesyesyesyes
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.SQL-like query languageSQL-99 for query and DML statementsnoyes
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
JDBC
Native API
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
HTTP APIJDBC
ODBC
Supported programming languagesC++
Java
Python
C
C#
C++
Go
Java
Python
Scala
.Net
C++
Java
Python
Scala
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesyesno
Triggersnoyesyes, event driven architecturenoyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-Clusterselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingIntegration with Hadoop and Sparkyes infoMap-Reduce pattern can be built with XAP task executorsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterEventual Consistency
Strong Consistency with Raft
Immediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency
Foreign keys infoReferential integrityno infonot needed in graphsnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyesyes
User concepts infoAccess controlAccess rights for users and rolesyesRole-based access controlsimple rights management via user accountsfine grained access rights according to SQL-standard

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More resources
AnzoGraph DBApache IoTDBGigaSpacesSiriDBYaacomo
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