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DBMS > AnzoGraph DB vs. eXtremeDB vs. FatDB vs. Google Cloud Bigtable

System Properties Comparison AnzoGraph DB vs. eXtremeDB vs. FatDB vs. Google Cloud Bigtable

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Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisoneXtremeDB  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Bigtable  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 virtualizationNatively in-memory DBMS with options for persistency, high-availability and clusteringA .NET NoSQL DBMS that can integrate with and extend SQL Server.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.
Primary database modelGraph DBMS
RDF store
Relational DBMS
Time Series DBMS
Document store
Key-value store
Key-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#307  Overall
#24  Graph DBMS
#13  RDF stores
Score0.74
Rank#223  Overall
#103  Relational DBMS
#18  Time Series DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Websitecambridgesemantics.com/­anzographwww.mcobject.comcloud.google.com/­bigtable
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmwww.mcobject.com/­docs/­extremedb.htmcloud.google.com/­bigtable/­docs
DeveloperCambridge SemanticsMcObjectFatCloudGoogle
Initial release2018200120122015
Current release2.3, January 20218.2, 2021
License infoCommercial or Open Sourcecommercial infofree trial version availablecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++C#
Server operating systemsLinuxAIX
HP-UX
Linux
macOS
Solaris
Windows
Windowshosted
Data schemeSchema-free and OWL/RDFS-schema supportyesschema-freeschema-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 availableno
Secondary indexesnoyesyesno
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.yes infowith the option: eXtremeSQLno infoVia inetgration in SQL Serverno
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
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languagesC++
Java
Python
.Net
C
C#
C++
Java
Lua
Python
Scala
C#C#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesyes infovia applicationsno
Triggersnoyes infoby defining eventsyes infovia applicationsno
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 factorInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingnoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integrityno infonot needed in graphsyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoAtomic single-row operations
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.yesyesno
User concepts infoAccess controlAccess rights for users and rolesno infoCan implement custom security layer via applicationsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)
More information provided by the system vendor
AnzoGraph DBeXtremeDBFatDBGoogle Cloud Bigtable
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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More resources
AnzoGraph DBeXtremeDBFatDBGoogle Cloud Bigtable
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