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DBMS > GigaSpaces vs. Google Cloud Bigtable vs. Stardog vs. TimesTen

System Properties Comparison GigaSpaces vs. Google Cloud Bigtable vs. Stardog vs. TimesTen

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Editorial information provided by DB-Engines
NameGigaSpaces  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonStardog  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionHigh 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.Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualizationAn in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.
Primary database modelDocument store
Object oriented DBMS infoValues are user defined objects
Key-value store
Wide column store
Graph DBMS
RDF store
Relational DBMS
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
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
Score1.93
Rank#121  Overall
#10  Graph DBMS
#6  RDF stores
Score1.26
Rank#164  Overall
#75  Relational DBMS
Websitewww.gigaspaces.comcloud.google.com/­bigtablewww.stardog.comwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmlcloud.google.com/­bigtable/­docsdocs.stardog.comdocs.oracle.com/­en/­database/­other-databases/­timesten/­index.html
DeveloperGigaspaces TechnologiesGoogleStardog-UnionOracle infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release2000201520101998
Current release15.5, September 20207.3.0, May 2020Release 22.1
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial licenses availablecommercialcommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/studentscommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetJava
Server operating systemsLinux
macOS
Solaris
Windows
hostedLinux
macOS
Windows
IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64
Data schemeschema-freeschema-freeschema-free and OWL/RDFS-schema supportyes
Typing infopredefined data types such as float or dateyesnoyesyes
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 metadatanono infoImport/export of XML data possibleno
Secondary indexesyesnoyes infosupports real-time indexing in full-text and geospatialyes
SQL infoSupport of SQLSQL-99 for query and DML statementsnoYes, compatible with all major SQL variants through dedicated BI/SQL Serveryes
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC
Supported programming languages.Net
C++
Java
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
C
C++
Java
Node.js
PL/SQL
Python
Server-side scripts infoStored proceduresyesnouser defined functions and aggregates, HTTP Server extensions in JavaPL/SQL
Triggersyes, event driven architecturenoyes infovia event handlersno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Internal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication in HA-ClusterMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency in HA-ClusterImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyes inforelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyes
User concepts infoAccess controlRole-based access controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and rolesfine grained access rights according to SQL-standard

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More resources
GigaSpacesGoogle Cloud BigtableStardogTimesTen
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