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DBMS > BaseX vs. Google Cloud Bigtable vs. GridDB vs. Sadas Engine

System Properties Comparison BaseX vs. Google Cloud Bigtable vs. GridDB vs. Sadas Engine

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Editorial information provided by DB-Engines
NameBaseX  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGridDB  Xexclude from comparisonSadas Engine  Xexclude from comparison
DescriptionLight-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Scalable in-memory time series database optimized for IoT and Big DataSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments
Primary database modelNative XML DBMSKey-value store
Wide column store
Time Series DBMSRelational 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
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Websitebasex.orgcloud.google.com/­bigtablegriddb.netwww.sadasengine.com
Technical documentationdocs.basex.orgcloud.google.com/­bigtable/­docsdocs.griddb.netwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperBaseX GmbHGoogleToshiba CorporationSADAS s.r.l.
Initial release2007201520132006
Current release10.7, August 20235.1, August 20228.0
License infoCommercial or Open SourceOpen Source infoBSD licensecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial infofree trial version available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C++
Server operating systemsLinux
OS X
Windows
hostedLinuxAIX
Linux
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateno infoXQuery supports typesnoyes infonumerical, string, blob, geometry, boolean, timestampyes
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.nonono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLnonoSQL92, SQL-like TQL (Toshiba Query Language)yes
APIs and other access methodsJava API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
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)
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-side scripts infoStored proceduresyesnonono
Triggersyes infovia eventsnoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesConnector 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 (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datamultiple readers, single writerAtomic single-row operationsACID at container level
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.noyesyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlUsers with fine-grained authorization concept on 4 levelsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users can be defined per databaseAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
BaseXGoogle Cloud BigtableGridDBSadas Engine
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
BaseXGoogle Cloud BigtableGridDBSadas Engine
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