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DBMS > AnzoGraph DB vs. Hive vs. RDFox vs. RRDtool vs. Spark SQL

System Properties Comparison AnzoGraph DB vs. Hive vs. RDFox vs. RRDtool vs. Spark SQL

Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonHive  Xexclude from comparisonRDFox  Xexclude from comparisonRRDtool  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationdata warehouse software for querying and managing large distributed datasets, built on HadoopHigh performance knowledge graph and semantic reasoning engineIndustry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database. infoThe data is stored in a circular buffer, thus the system storage footprint remains constant over time.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelGraph DBMS
RDF store
Relational DBMSGraph DBMS
RDF store
Time Series DBMSRelational DBMS
Secondary database modelsRelational 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
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score0.29
Rank#300  Overall
#24  Graph DBMS
#13  RDF stores
Score1.90
Rank#132  Overall
#11  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitecambridgesemantics.com/­anzographhive.apache.orgwww.oxfordsemantic.techoss.oetiker.ch/­rrdtoolspark.apache.org/­sql
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.oxfordsemantic.techoss.oetiker.ch/­rrdtool/­docspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCambridge SemanticsApache Software Foundation infoinitially developed by FacebookOxford Semantic TechnologiesTobias OetikerApache Software Foundation
Initial release20182012201719992014
Current release2.3, January 20213.1.3, April 20226.0, Septermber 20221.8.0, 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoApache Version 2commercialOpen Source infoGPL V2 and FLOSSOpen Source infoApache 2.0
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 languageJavaC++C infoImplementations in Java (e.g. RRD4J) and C# availableScala
Server operating systemsLinuxAll OS with a Java VMLinux
macOS
Windows
HP-UX
Linux
Linux
OS X
Windows
Data schemeSchema-free and OWL/RDFS-schema supportyesyes infoRDF schemasyesyes
Typing infopredefined data types such as float or dateyesyesNumeric data onlyyes
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.nono infoExporting into and restoring from XML files possibleno
Secondary indexesnoyesnono
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.SQL-like DML and DDL statementsnonoSQL-like DML and DDL statements
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
JDBC
ODBC
Thrift
RESTful HTTP API
SPARQL 1.1
in-process shared library
Pipes
JDBC
ODBC
Supported programming languagesC++
Java
Python
C++
Java
PHP
Python
C
Java
C infowith librrd library
C# infowith a different implementation of RRDTool
Java infowith a different implementation of RRDTool
JavaScript (Node.js) infowith a different implementation of RRDTool
Lua
Perl
PHP infowith a wrapper library
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infouser defined functions and integration of map-reducenono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-Clusterselectable replication factorreplication via a shared file systemnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterEventual ConsistencyImmediate Consistency in stand-alone mode, Eventual Consistency in replicated setupsnone
Foreign keys infoReferential integrityno infonot needed in graphsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoby using the rrdcached daemonyes
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.yesyesyesno
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and rolesRoles, resources, and access typesnono

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More resources
AnzoGraph DBHiveRDFoxRRDtoolSpark SQL
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