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DBMS > AnzoGraph DB vs. GigaSpaces vs. Google Cloud Spanner vs. Realm

System Properties Comparison AnzoGraph DB vs. GigaSpaces vs. Google Cloud Spanner vs. Realm

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Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonGigaSpaces  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonRealm  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 TransactionsA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data
Primary database modelGraph DBMS
RDF store
Document store
Object oriented DBMS infoValues are user defined objects
Relational DBMSDocument store
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#307  Overall
#24  Graph DBMS
#13  RDF stores
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score7.60
Rank#52  Overall
#9  Document stores
Websitecambridgesemantics.com/­anzographwww.gigaspaces.comcloud.google.com/­spannerrealm.io
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmdocs.gigaspaces.com/­latest/­landing.htmlcloud.google.com/­spanner/­docsrealm.io/­docs
DeveloperCambridge SemanticsGigaspaces TechnologiesGoogleRealm, acquired by MongoDB in May 2019
Initial release2018200020172014
Current release2.3, January 202115.5, September 2020
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoApache Version 2; Commercial licenses availablecommercialOpen Source
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .Net
Server operating systemsLinuxLinux
macOS
Solaris
Windows
hostedAndroid
Backend: server-less
iOS
Windows
Data schemeSchema-free and OWL/RDFS-schema supportschema-freeyesyes
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.nono infoXML can be used for describing objects metadatanono
Secondary indexesnoyesyesyes
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.SQL-99 for query and DML statementsyes infoQuery statements complying to ANSI 2011no
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
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Supported programming languagesC++
Java
Python
.Net
C++
Java
Python
Scala
Go
Java
JavaScript (Node.js)
Python
.Net
Java infowith Android only
Objective-C
React Native
Swift
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesnono inforuns within the applications so server-side scripts are unnecessary
Triggersnoyes, event driven architecturenoyes infoChange Listeners
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
Multi-source replication with 3 replicas for regional instances.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingyes infoMap-Reduce pattern can be built with XAP task executorsyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infonot needed in graphsnoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoStrict serializable isolationACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.yesyesnoyes infoIn-Memory realm
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

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More resources
AnzoGraph DBGigaSpacesGoogle Cloud SpannerRealm
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