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DBMS > BaseX vs. GridDB vs. Splice Machine vs. Teradata Aster vs. TinkerGraph

System Properties Comparison BaseX vs. GridDB vs. Splice Machine vs. Teradata Aster vs. TinkerGraph

Editorial information provided by DB-Engines
NameBaseX  Xexclude from comparisonGridDB  Xexclude from comparisonSplice Machine  Xexclude from comparisonTeradata Aster  Xexclude from comparisonTinkerGraph  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionLight-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.Scalable in-memory time series database optimized for IoT and Big DataOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkPlatform for big data analytics on multistructured data sources and typesA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API
Primary database modelNative XML DBMSTime Series DBMSRelational DBMSRelational DBMSGraph DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.73
Rank#142  Overall
#4  Native XML DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.08
Rank#348  Overall
#35  Graph DBMS
Websitebasex.orggriddb.netsplicemachine.comtinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlin
Technical documentationdocs.basex.orgdocs.griddb.netsplicemachine.com/­how-it-works
DeveloperBaseX GmbHToshiba CorporationSplice MachineTeradata
Initial release20072013201420052009
Current release10.7, August 20235.1, August 20223.1, March 2021
License infoCommercial or Open SourceOpen Source infoBSD licenseOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoAGPL 3.0, commercial license availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++JavaJava
Server operating systemsLinux
OS X
Windows
LinuxLinux
OS X
Solaris
Windows
Linux
Data schemeschema-freeyesyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeschema-free
Typing infopredefined data types such as float or dateno infoXQuery supports typesyes infonumerical, string, blob, geometry, boolean, timestampyesyesyes
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.noyes infoin Aster File Storeno
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)yesyesno
APIs and other access methodsJava API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
Native Spark Datasource
ODBC
ADO.NET
JDBC
ODBC
OLE DB
TinkerPop 3
Supported programming languagesActionscript
C
C#
Haskell
Java
JavaScript infoNode.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C
C#
C++
Java
Python
R
Groovy
Java
Server-side scripts infoStored proceduresyesnoyes infoJavaR packagesno
Triggersyes infovia eventsyesyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShared Nothhing Auto-Sharding, Columnar PartitioningShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationMulti-source replication
Source-replica replication
yes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsYes, via Full Spark Integrationyes infoSQL Map-Reduce Frameworkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationnone
Foreign keys infoReferential integritynonoyesnoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datamultiple readers, single writerACID at container levelACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesno
Durability infoSupport for making data persistentyesyesyesyesoptional
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes
User concepts infoAccess controlUsers with fine-grained authorization concept on 4 levelsAccess rights for users can be defined per databaseAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standardno
More information provided by the system vendor
BaseXGridDBSplice MachineTeradata AsterTinkerGraph
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
BaseXGridDBSplice MachineTeradata AsterTinkerGraph
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