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DBMS > GridDB vs. Sadas Engine vs. TimescaleDB vs. Warp 10

System Properties Comparison GridDB vs. Sadas Engine vs. TimescaleDB vs. Warp 10

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonSadas Engine  Xexclude from comparisonTimescaleDB  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionScalable 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 time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelTime Series DBMSRelational DBMSTime Series DBMSTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Score0.07
Rank#349  Overall
#32  Time Series DBMS
Websitegriddb.netwww.sadasengine.comwww.timescale.comwww.warp10.io
Technical documentationdocs.griddb.netwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationdocs.timescale.comwww.warp10.io/­content/­02_Getting_started
DeveloperToshiba CorporationSADAS s.r.l.TimescaleSenX
Initial release2013200620172015
Current release5.1, August 20228.02.13.0, November 2023
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial infofree trial version availableOpen Source infoApache 2.0Open Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++CJava
Server operating systemsLinuxAIX
Linux
Windows
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyes
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.nonoyesno
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)yesyes infofull PostgreSQL SQL syntaxno
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP API
Jupyter
WebSocket
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C#
C++
Groovy
Java
PHP
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnonouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellyes infoWarpScript
Triggersyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningyes, across time and space (hash partitioning) attributesSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneSource-replica replication with hot standby and reads on replicas infoselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate ConsistencyImmediate Consistency infobased on HBase
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelACIDno
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.yesyes infomanaged by 'Learn by Usage'noyes
User concepts infoAccess controlAccess rights for users can be defined per databaseAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standardMandatory use of cryptographic tokens, containing fine-grained authorizations
More information provided by the system vendor
GridDBSadas EngineTimescaleDBWarp 10
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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GridDBSadas EngineTimescaleDBWarp 10
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