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DBMS > AnzoGraph DB vs. GigaSpaces vs. Google Cloud Bigtable vs. ObjectBox

System Properties Comparison AnzoGraph DB vs. GigaSpaces vs. Google Cloud Bigtable vs. ObjectBox

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Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonGigaSpaces  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonObjectBox  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors
Primary database modelGraph DBMS
RDF store
Document store
Object oriented DBMS infoValues are user defined objects
Key-value store
Wide column store
Object oriented DBMS
Vector DBMS
Secondary database modelsGraph DBMS
Search engine
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#302  Overall
#24  Graph DBMS
#13  RDF stores
Score0.91
Rank#197  Overall
#33  Document stores
#7  Object oriented DBMS
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score1.08
Rank#179  Overall
#6  Object oriented DBMS
#9  Vector DBMS
Websitecambridgesemantics.com/­anzographwww.gigaspaces.comcloud.google.com/­bigtablegithub.com/­objectbox
objectbox.io
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmdocs.gigaspaces.com/­latest/­landing.htmlcloud.google.com/­bigtable/­docsdocs.objectbox.io
DeveloperCambridge SemanticsGigaspaces TechnologiesGoogleObjectBox Limited
Initial release2018200020152017
Current release2.3, January 202115.5, September 20204.0 (May 2024)
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoApache Version 2; Commercial licenses availablecommercialBindings are released under Apache 2.0 infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetC and C++
Server operating systemsLinuxLinux
macOS
Solaris
Windows
hostedAndroid
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows
Data schemeSchema-free and OWL/RDFS-schema supportschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnoyes, plus "flex" map-like types
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 infoXML can be used for describing objects metadatanono
Secondary indexesnoyesnoyes
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.SQL-99 for query and DML statementsnono
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Proprietary native API
Supported programming languagesC++
Java
Python
.Net
C++
Java
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesnono
Triggersnoyes, event driven architecturenono
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-ClusterMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Internal replication in Colossus, and regional replication between two clusters in different zonesData sync between devices allowing occasional connected databases to work completely offline
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingyes infoMap-Reduce pattern can be built with XAP task executorsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integrityno infonot needed in graphsnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic single-row operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesyesnono
User concepts infoAccess controlAccess rights for users and rolesRole-based access controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes
More information provided by the system vendor
AnzoGraph DBGigaSpacesGoogle Cloud BigtableObjectBox
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More resources
AnzoGraph DBGigaSpacesGoogle Cloud BigtableObjectBox
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