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DBMS > GridDB vs. Qdrant vs. Sadas Engine

System Properties Comparison GridDB vs. Qdrant vs. Sadas Engine

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonQdrant  Xexclude from comparisonSadas Engine  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataA high-performance vector database with neural network or semantic-based matchingSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments
Primary database modelTime Series DBMSVector DBMSRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score1.16
Rank#175  Overall
#6  Vector DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Websitegriddb.netgithub.com/­qdrant/­qdrant
qdrant.tech
www.sadasengine.com
Technical documentationdocs.griddb.netqdrant.tech/­documentationwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperToshiba CorporationQdrantSADAS s.r.l.
Initial release201320212006
Current release5.1, August 20228.0
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2.0commercial infofree trial version available
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++RustC++
Server operating systemsLinuxDocker
Linux
macOS
Windows
AIX
Linux
Windows
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampNumbers, Strings, Geo, Booleanyes
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 infoKeywords, numberic ranges, geo, full-textyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)noyes
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
gRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
JDBC
ODBC
Proprietary protocol
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-side scripts infoStored proceduresnono
Triggersyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationCollection-level replicationnone
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 containersEventual Consistency, tunable consistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container level
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.yesyesyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlAccess rights for users can be defined per databaseKey-based authenticationAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
GridDBQdrantSadas 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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
GridDBQdrantSadas Engine
Recent citations in the news

General Availability of GridDB® 5.5 Enterprise Edition ~Enhancing the efficiency of IoT system development and ...
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GridDB Use case Large-scale high-speed processing of smart meter data following the deregulation of electrical power ...
1 November 2020, global.toshiba

Toshiba's Distributed Database GridDB(R) Now Features Scale-Out and Scale-Up combo for Petabyte-scale Data ...
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Qdrant launches first vector database as a managed hybrid cloud
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