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DBMS > AnzoGraph DB vs. Apache IoTDB vs. eXtremeDB vs. FatDB

System Properties Comparison AnzoGraph DB vs. Apache IoTDB vs. eXtremeDB vs. FatDB

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Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonApache IoTDB  Xexclude from comparisoneXtremeDB  Xexclude from comparisonFatDB  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the 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 FlinkNatively in-memory DBMS with options for persistency, high-availability and clusteringA .NET NoSQL DBMS that can integrate with and extend SQL Server.
Primary database modelGraph DBMS
RDF store
Time Series DBMSRelational DBMS
Time Series DBMS
Document store
Key-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.27
Rank#302  Overall
#24  Graph DBMS
#13  RDF stores
Score1.19
Rank#176  Overall
#15  Time Series DBMS
Score0.73
Rank#227  Overall
#104  Relational DBMS
#18  Time Series DBMS
Websitecambridgesemantics.com/­anzographiotdb.apache.orgwww.mcobject.com
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.mcobject.com/­docs/­extremedb.htm
DeveloperCambridge SemanticsApache Software FoundationMcObjectFatCloud
Initial release2018201820012012
Current release2.3, January 20211.1.0, April 20238.2, 2021
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoApache Version 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC and C++C#
Server operating systemsLinuxAll OS with a Java VM (>= 1.8)AIX
HP-UX
Linux
macOS
Solaris
Windows
Windows
Data schemeSchema-free and OWL/RDFS-schema supportyesyesschema-free
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.nonono infosupport of XML interfaces available
Secondary indexesnoyesyesyes
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.SQL-like query languageyes infowith the option: eXtremeSQLno infoVia inetgration in SQL Server
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
JDBC
Native API
.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Supported programming languagesC++
Java
Python
C
C#
C++
Go
Java
Python
Scala
.Net
C
C#
C++
Java
Lua
Python
Scala
C#
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesyesyes infovia applications
Triggersnoyesyes infoby defining eventsyes infovia applications
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioning / shardingSharding
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 replicasActive 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 factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingIntegration with Hadoop and Sparknoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityno infonot needed in graphsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyes
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.yesyesyes
User concepts infoAccess controlAccess rights for users and rolesyesno infoCan implement custom security layer via applications
More information provided by the system vendor
AnzoGraph DBApache IoTDBeXtremeDBFatDB
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...
» more
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...
» more

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AnzoGraph DBApache IoTDBeXtremeDBFatDB
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