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DBMS > AnzoGraph DB vs. Apache IoTDB vs. Cubrid vs. GBase vs. IBM Db2 Event Store

System Properties Comparison AnzoGraph DB vs. Apache IoTDB vs. Cubrid vs. GBase vs. IBM Db2 Event Store

Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonApache IoTDB  Xexclude from comparisonCubrid  Xexclude from comparisonGBase  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparison
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 FlinkCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.Distributed Event Store optimized for Internet of Things use cases
Primary database modelGraph DBMS
RDF store
Time Series DBMSRelational DBMSRelational DBMSEvent Store
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#307  Overall
#24  Graph DBMS
#13  RDF stores
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score1.20
Rank#169  Overall
#78  Relational DBMS
Score1.07
Rank#185  Overall
#86  Relational DBMS
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Websitecambridgesemantics.com/­anzographiotdb.apache.orgcubrid.com (korean)
cubrid.org (english)
www.gbase.cnwww.ibm.com/­products/­db2-event-store
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlcubrid.org/­manualswww.ibm.com/­docs/­en/­db2-event-store
DeveloperCambridge SemanticsApache Software FoundationCUBRID Corporation, CUBRID FoundationGeneral Data Technology Co., Ltd.IBM
Initial release20182018200820042017
Current release2.3, January 20211.1.0, April 202311.0, January 2021GBase 8a, GBase 8s, GBase 8c2.0
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoApache Version 2.0Open Source infoApache Version 2.0commercialcommercial infofree developer edition available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++, JavaC, Java, PythonC and C++
Server operating systemsLinuxAll OS with a Java VM (>= 1.8)Linux
Windows
LinuxLinux infoLinux, macOS, Windows for the developer addition
Data schemeSchema-free and OWL/RDFS-schema supportyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nononoyesno
Secondary indexesnoyesyesyesno
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.SQL-like query languageyesStandard with numerous extensionsyes infothrough the embedded Spark runtime
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
JDBC
Native API
ADO.NET
JDBC
ODBC
OLE DB
ADO.NET
C API
JDBC
ODBC
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC++
Java
Python
C
C#
C++
Go
Java
Python
Scala
C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesJava Stored Proceduresuser defined functionsyes
Triggersnoyesyesyesno
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)nonehorizontal partitioning (by range, list and hash) and vertical partitioningSharding
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 replicasSource-replica replicationyesActive-active shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingIntegration with Hadoop and Sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityno infonot needed in graphsnoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesNo - written data is immutable
Durability infoSupport for making data persistentyesyesyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes
User concepts infoAccess controlAccess rights for users and rolesyesfine grained access rights according to SQL-standardyesfine grained access rights according to SQL-standard

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More resources
AnzoGraph DBApache IoTDBCubridGBaseIBM Db2 Event Store
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