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DBMS > GridDB vs. Sadas Engine vs. VictoriaMetrics

System Properties Comparison GridDB vs. Sadas Engine vs. VictoriaMetrics

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonSadas Engine  Xexclude from comparisonVictoriaMetrics  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 fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelTime Series DBMSRelational DBMSTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.23
Rank#159  Overall
#11  Time Series DBMS
Score0.00
Rank#354  Overall
#152  Relational DBMS
Score0.58
Rank#223  Overall
#17  Time Series DBMS
Websitegriddb.netwww.sadasengine.comvictoriametrics.com
Technical documentationdocs.griddb.netwww.sadasengine.com/­index.php/­downloads/­documentation-columnar-dbdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperToshiba CorporationSADAS s.r.l.VictoriaMetrics
Initial release201320062018
Current release4.6, February 20218.0v1.72, January 2022
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 Version 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++Go
Server operating systemsLinuxAIX
Linux
Windows
FreeBSD
Linux
macOS
OpenBSD
Data schemeyesyes
Typing infopredefined data types such as float or dateyes 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 indexesyesyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)yesno
APIs and other access methodsProprietary protocolJDBC
ODBC
Proprietary protocol
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-side scripts infoStored proceduresnonono
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector 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 within container, eventual consistency across containersImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
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'no
User concepts infoAccess controlAccess 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
GridDBSadas EngineVictoriaMetrics
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
High performance, horizontally scalable time series database and monitoring solution...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Specifically designed for highly loaded workloads Addresses most of the scalability...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
When the current monitoring solution can't keep up with increasing workload Kubernetes...
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Grammarly, Wix.com, adidas, Sensedia, Brandwatch, CERN, COLOPL, Razorpay See our...
» more
Market metricsGitHub trending repository
» more
6k stars and 100+ contributors on GitHub 45M+ downloads Thousands of active users...
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
VictoriaMetrics comes in three versions: an open source version, an Enterprise version...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
GridDBSadas EngineVictoriaMetrics
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