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DBMS > AnzoGraph DB vs. Apache Drill vs. Apache IoTDB vs. PostgreSQL

System Properties Comparison AnzoGraph DB vs. Apache Drill vs. Apache IoTDB vs. PostgreSQL

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Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonApache Drill  Xexclude from comparisonApache IoTDB  Xexclude from comparisonPostgreSQL  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationSchema-free SQL Query Engine for Hadoop, NoSQL and Cloud StorageAn 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 SQL
Primary database modelGraph DBMS
RDF store
Document store
Relational DBMS
Time Series DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.
Secondary database modelsDocument store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#303  Overall
#25  Graph DBMS
#14  RDF stores
Score2.02
Rank#124  Overall
#22  Document stores
#59  Relational DBMS
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score636.25
Rank#4  Overall
#4  Relational DBMS
Websitecambridgesemantics.com/­anzographdrill.apache.orgiotdb.apache.orgwww.postgresql.org
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmdrill.apache.org/­docsiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.postgresql.org/­docs
DeveloperCambridge SemanticsApache Software FoundationApache Software FoundationPostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release2018201220181989 info1989: Postgres, 1996: PostgreSQL
Current release2.3, January 20211.20.3, January 20231.1.0, April 202316.3, May 2024
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoBSD
Cloud-based only infoOnly available as a cloud servicenononono
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Implementation languageJavaC
Server operating systemsLinuxLinux
OS X
Windows
All OS with a Java VM (>= 1.8)FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeSchema-free and OWL/RDFS-schema supportschema-freeyesyes
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.nononoyes infospecific XML-type available, but no XML query functionality.
Secondary indexesnonoyesyes
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.SQL SELECT statement is SQL:2003 compliantSQL-like query languageyes infostandard with numerous extensions
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
JDBC
ODBC
RESTful HTTP API
JDBC
Native API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC++
Java
Python
C++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 aggregatesuser defined functionsyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)partitioning by range, list and (since PostgreSQL 11) by hash
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 extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingyesIntegration with Hadoop and Sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusternoneEventual Consistency
Strong Consistency with Raft
Immediate Consistency
Foreign keys infoReferential integrityno infonot needed in graphsnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesDepending on the underlying data sourceyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesDepending on the underlying data sourceyesno
User concepts infoAccess controlAccess rights for users and rolesDepending on the underlying data sourceyesfine grained access rights according to SQL-standard

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More resources
AnzoGraph DBApache DrillApache IoTDBPostgreSQL
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