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DBMS > Amazon DocumentDB vs. GridDB vs. Manticore Search vs. Qdrant

System Properties Comparison Amazon DocumentDB vs. GridDB vs. Manticore Search vs. Qdrant

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonGridDB  Xexclude from comparisonManticore Search  Xexclude from comparisonQdrant  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceScalable in-memory time series database optimized for IoT and Big DataMulti-storage database for search, including full-text search.A high-performance vector database with neural network or semantic-based matching
Primary database modelDocument storeTime Series DBMSSearch engineVector DBMS
Secondary database modelsKey-value store
Relational DBMS
Time Series DBMS infousing the Manticore Columnar Library
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score0.29
Rank#302  Overall
#21  Search engines
Score1.28
Rank#167  Overall
#8  Vector DBMS
Websiteaws.amazon.com/­documentdbgriddb.netmanticoresearch.comgithub.com/­qdrant/­qdrant
qdrant.tech
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.griddb.netmanual.manticoresearch.comqdrant.tech/­documentation
DeveloperToshiba CorporationManticore SoftwareQdrant
Initial release2019201320172021
Current release5.1, August 20226.0, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoGPL version 2Open Source infoApache Version 2.0
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++Rust
Server operating systemshostedLinuxFreeBSD
Linux
macOS
Windows
Docker
Linux
macOS
Windows
Data schemeschema-freeyesFixed schemaschema-free
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, BooleanNumbers, Strings, Geo, Boolean
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.nonoCan index from XMLno
Secondary indexesyesyesyes infofull-text index on all search fieldsyes infoKeywords, numberic ranges, geo, full-text
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query languageno
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
gRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresnonouser defined functions
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasSource-replica replicationSynchronous replication based on Galera libraryCollection-level replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersEventual Consistency, tunable consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACID at container levelyes infoisolated transactions for atomic changes and binary logging for safe writes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Manticore index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users can be defined per databasenoKey-based authentication
More information provided by the system vendor
Amazon DocumentDBGridDBManticore SearchQdrant
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
Amazon DocumentDBGridDBManticore SearchQdrant
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