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DBMS > AnzoGraph DB vs. Apache IoTDB vs. H2 vs. IBM Db2 Event Store vs. JSqlDb

System Properties Comparison AnzoGraph DB vs. Apache IoTDB vs. H2 vs. IBM Db2 Event Store vs. JSqlDb

Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonApache IoTDB  Xexclude from comparisonH2  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonJSqlDb  Xexclude from comparison
JSqlDB seems to be discontinued. Therefore it is excluded 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 FlinkFull-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.Distributed Event Store optimized for Internet of Things use casesJavaScript Query Language Database, stores JavaScript objects and primitives
Primary database modelGraph DBMS
RDF store
Time Series DBMSRelational DBMSEvent Store
Time Series DBMS
Document store
Object oriented DBMS
Secondary database modelsSpatial 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
Score8.13
Rank#49  Overall
#31  Relational DBMS
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Websitecambridgesemantics.com/­anzographiotdb.apache.orgwww.h2database.comwww.ibm.com/­products/­db2-event-storejsqldb.org (offline)
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.h2database.com/­html/­main.htmlwww.ibm.com/­docs/­en/­db2-event-store
DeveloperCambridge SemanticsApache Software FoundationThomas MuellerIBMKonrad von Backstrom
Initial release20182018200520172018
Current release2.3, January 20211.1.0, April 20232.2.220, July 20232.00.8, December 2018
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoApache Version 2.0Open Source infodual-licence (Mozilla public license, Eclipse public license)commercial infofree developer edition availableOpen Source
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC and C++
Server operating systemsLinuxAll OS with a Java VM (>= 1.8)All OS with a Java VMLinux infoLinux, macOS, Windows for the developer additionLinux
macOS
Windows
Data schemeSchema-free and OWL/RDFS-schema supportyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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.nonononono
Secondary indexesnoyesyesnono
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.SQL-like query languageyesyes infothrough the embedded Spark runtimeno
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
JDBC
Native API
JDBC
ODBC
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC++
Java
Python
C
C#
C++
Go
Java
Python
Scala
JavaC
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
JavaScript
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesJava Stored Procedures and User-Defined Functionsyesfunctions in JavaScript
Triggersnoyesyesnono
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneShardingnone
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 replicasWith clustering: 2 database servers on different computers operate on identical copies of a databaseActive-active shard replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingIntegration with Hadoop and Sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityno infonot needed in graphsnoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)No - written data is immutable
Durability infoSupport for making data persistentyesyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes infousing RocksDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes
User concepts infoAccess controlAccess rights for users and rolesyesfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
AnzoGraph DBApache IoTDBH2IBM Db2 Event StoreJSqlDb
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