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DBMS > AnzoGraph DB vs. eXtremeDB vs. Hive vs. RavenDB

System Properties Comparison AnzoGraph DB vs. eXtremeDB vs. Hive vs. RavenDB

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Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisoneXtremeDB  Xexclude from comparisonHive  Xexclude from comparisonRavenDB  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationNatively in-memory DBMS with options for persistency, high-availability and clusteringdata warehouse software for querying and managing large distributed datasets, built on HadoopOpen Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelGraph DBMS
RDF store
Relational DBMS
Time Series DBMS
Relational DBMSDocument store
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series 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
Score0.80
Rank#214  Overall
#99  Relational DBMS
#18  Time Series DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score2.84
Rank#101  Overall
#18  Document stores
Websitecambridgesemantics.com/­anzographwww.mcobject.comhive.apache.orgravendb.net
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmwww.mcobject.com/­docs/­extremedb.htmcwiki.apache.org/­confluence/­display/­Hive/­Homeravendb.net/­docs
DeveloperCambridge SemanticsMcObjectApache Software Foundation infoinitially developed by FacebookHibernating Rhinos
Initial release2018200120122010
Current release2.3, January 20218.2, 20213.1.3, April 20225.4, July 2022
License infoCommercial or Open Sourcecommercial infofree trial version availablecommercialOpen Source infoApache Version 2Open Source infoAGPL version 3, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++JavaC#
Server operating systemsLinuxAIX
HP-UX
Linux
macOS
Solaris
Windows
All OS with a Java VMLinux
macOS
Raspberry Pi
Windows
Data schemeSchema-free and OWL/RDFS-schema supportyesyesschema-free
Typing infopredefined data types such as float or dateyesyesno
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 infosupport of XML interfaces available
Secondary indexesnoyesyesyes
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.yes infowith the option: eXtremeSQLSQL-like DML and DDL statementsSQL-like query language (RQL)
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
JDBC
ODBC
Thrift
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Supported programming languagesC++
Java
Python
.Net
C
C#
C++
Java
Lua
Python
Scala
C++
Java
PHP
Python
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesyes infouser defined functions and integration of map-reduceyes
Triggersnoyes infoby defining eventsnoyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardinghorizontal partitioning / shardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-ClusterActive Replication Fabricâ„¢ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
selectable replication factorMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingnoyes infoquery execution via MapReduceyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterImmediate ConsistencyEventual ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integrityno infonot needed in graphsyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID, Cluster-wide transaction available
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyes
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.yesyes
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and rolesAuthorization levels configured per client per database
More information provided by the system vendor
AnzoGraph DBeXtremeDBHiveRavenDB
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
» more
Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more
Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more
Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
» more
Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
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AnzoGraph DBeXtremeDBHiveRavenDB
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