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

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

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonGridDB  Xexclude from comparisonSadas Engine  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionGoogle'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 environmentsA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelKey-value store
Wide column store
Time Series DBMSRelational DBMSDocument store
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.84
Rank#80  Overall
#13  Key-value stores
#6  Wide column stores
Score1.25
Rank#157  Overall
#12  Time Series DBMS
Score0.00
Rank#357  Overall
#155  Relational DBMS
Score0.00
Rank#357  Overall
#47  Document stores
Websitecloud.google.com/­bigtablegriddb.netwww.sadasengine.comgithub.com/­xtdb/­xtdb
xtdb.com
Technical documentationcloud.google.com/­bigtable/­docsdocs.griddb.netwww.sadasengine.com/­index.php/­downloads/­documentation-columnar-dbxtdb.com/­docs
DeveloperGoogleToshiba CorporationSADAS s.r.l.Juxt Ltd.
Initial release2015201320062019
Current release4.6, February 20218.01.19, September 2021
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial infofree trial version availableOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++Clojure
Server operating systemshostedLinuxAIX
Linux
Windows
All OS with a Java 8 (and higher) VM
Linux
Data schemeschema-freeyesyesschema-free
Typing infopredefined data types such as float or datenoyes infonumerical, string, blob, geometry, boolean, timestampyesyes, extensible-data-notation format
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.nononono
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)yeslimited SQL, making use of Apache Calcite
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Proprietary protocolJDBC
ODBC
Proprietary protocol
HTTP REST
JDBC
Supported programming languagesC#
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
Clojure
Java
Server-side scripts infoStored proceduresnononono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationnoneyes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
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 integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACID at container levelACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
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 controlAccess 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
Google Cloud BigtableGridDBSadas EngineXTDB infoformerly named Crux
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
Google Cloud BigtableGridDBSadas EngineXTDB infoformerly named Crux
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