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DBMS > GigaSpaces vs. Google BigQuery vs. GraphDB vs. GridDB vs. Sphinx

System Properties Comparison GigaSpaces vs. Google BigQuery vs. GraphDB vs. GridDB vs. Sphinx

Editorial information provided by DB-Engines
NameGigaSpaces  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonGraphDB infoformer name: OWLIM  Xexclude from comparisonGridDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsLarge scale data warehouse service with append-only tablesEnterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.Scalable in-memory time series database optimized for IoT and Big DataOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument store
Object oriented DBMS infoValues are user defined objects
Relational DBMSGraph DBMS
RDF store
Time Series DBMSSearch engine
Secondary database modelsGraph DBMS
Search engine
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.02
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score61.90
Rank#19  Overall
#13  Relational DBMS
Score3.10
Rank#100  Overall
#7  Graph DBMS
#4  RDF stores
Score2.02
Rank#132  Overall
#11  Time Series DBMS
Score6.03
Rank#60  Overall
#6  Search engines
Websitewww.gigaspaces.comcloud.google.com/­bigquerywww.ontotext.comgriddb.netsphinxsearch.com
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmlcloud.google.com/­bigquery/­docsgraphdb.ontotext.com/­documentationdocs.griddb.netsphinxsearch.com/­docs
Social network pagesLinkedInTwitterYouTubeGitHubMedium
DeveloperGigaspaces TechnologiesGoogleOntotextToshiba CorporationSphinx Technologies Inc.
Initial release20002010200020132001
Current release15.5, September 202010.4, October 20235.1, August 20223.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial licenses availablecommercialcommercial infoSome plugins of GraphDB Workbench are open sourcedOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetJavaC++C++
Server operating systemsLinux
macOS
Solaris
Windows
hostedAll OS with a Java VM
Linux
OS X
Windows
LinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesschema-free and OWL/RDFS-schema support; RDF shapesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes infonumerical, string, blob, geometry, boolean, timestampno
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.no infoXML can be used for describing objects metadatanonono
Secondary indexesyesnoyes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-99 for query and DML statementsyesstored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBCSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query language (SphinxQL)
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
RESTful HTTP/JSON APIGeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Proprietary protocol
Supported programming languages.Net
C++
Java
Python
Scala
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyesuser defined functions infoin JavaScriptwell-defined plugin interfaces; JavaScript server-side extensibilitynono
Triggersyes, event driven architecturenonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnonenoneShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Multi-source replicationSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsnonoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate ConsistencyImmediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)Immediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integritynonoyes infoConstraint checkingnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infoSince BigQuery is designed for querying dataACIDACID at container levelno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlRole-based access controlAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.Access rights for users can be defined per databaseno
More information provided by the system vendor
GigaSpacesGoogle BigQueryGraphDB infoformer name: OWLIMGridDBSphinx
Specific characteristicsOntotext GraphDB is a semantic database engine that allows organizations to build...
» more
GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantagesGraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
» more
1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosMetadata enrichment and management, linked data publishing, semantic inferencing...
» more
Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customers​ GraphDB provides a platform for building next-generation AI and Knowledge Graph...
» more
Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGraphDB is the most utilized semantic triplestore for mission-critical enterprise...
» more
GitHub trending repository
» more
Licensing and pricing modelsGraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition...
» more
Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
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More resources
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