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DBMS > AnzoGraph DB vs. Apache IoTDB vs. PostgreSQL vs. SAP HANA

System Properties Comparison AnzoGraph DB vs. Apache IoTDB vs. PostgreSQL vs. SAP HANA

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Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonApache IoTDB  Xexclude from comparisonPostgreSQL  Xexclude from comparisonSAP HANA  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 FlinkWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLIn-memory, column based data store. Available as appliance or cloud service
Primary database modelGraph DBMS
RDF store
Time Series DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Relational DBMS
Secondary database modelsDocument store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
Document store
Graph DBMS infowith SAP Hana, Enterprise Edition
Spatial DBMS
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
Score636.25
Rank#4  Overall
#4  Relational DBMS
Score44.27
Rank#23  Overall
#16  Relational DBMS
Websitecambridgesemantics.com/­anzographiotdb.apache.orgwww.postgresql.orgwww.sap.com/­products/­hana.html
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.postgresql.org/­docshelp.sap.com/­hana
DeveloperCambridge SemanticsApache Software FoundationPostgreSQL Global Development Group infowww.postgresql.org/­developerSAP
Initial release201820181989 info1989: Postgres, 1996: PostgreSQL2010
Current release2.3, January 20211.1.0, April 202316.3, May 20242.0 SPS07 (AprilĀ 4, 2023), April 2023
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoApache Version 2.0Open Source infoBSDcommercial
Cloud-based only infoOnly available as a cloud servicenononono infoalso available as a cloud based service
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC
Server operating systemsLinuxAll OS with a Java VM (>= 1.8)FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Appliance or cloud-service
Data schemeSchema-free and OWL/RDFS-schema supportyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.nonoyes infospecific XML-type available, but no XML query functionality.no
Secondary indexesnoyesyesyes
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.SQL-like query languageyes infostandard with numerous extensionsyes
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
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Supported programming languagesC++
Java
Python
C
C#
C++
Go
Java
Python
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.SQLScript, R
Triggersnoyesyesyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)partitioning by range, list and (since PostgreSQL 11) by hashyes
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 replication infoother methods possible by using 3rd party extensionsyes
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 Consistency
Foreign keys infoReferential integrityno infonot needed in graphsnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
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-standardyes

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More resources
AnzoGraph DBApache IoTDBPostgreSQLSAP HANA
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