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DBMS > Amazon DocumentDB vs. Apache Druid vs. GridDB vs. Manticore Search

System Properties Comparison Amazon DocumentDB vs. Apache Druid vs. GridDB vs. Manticore Search

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache Druid  Xexclude from comparisonGridDB  Xexclude from comparisonManticore Search  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataScalable in-memory time series database optimized for IoT and Big DataMulti-storage database for search, including full-text search.
Primary database modelDocument storeRelational DBMS
Time Series DBMS
Time Series DBMSSearch engine
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
Score1.89
Rank#137  Overall
#24  Document stores
Score3.29
Rank#95  Overall
#49  Relational DBMS
#7  Time Series DBMS
Score2.02
Rank#132  Overall
#11  Time Series DBMS
Score0.23
Rank#317  Overall
#21  Search engines
Websiteaws.amazon.com/­documentdbdruid.apache.orggriddb.netmanticoresearch.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdruid.apache.org/­docs/­latest/­designdocs.griddb.netmanual.manticoresearch.com
DeveloperApache Software Foundation and contributorsToshiba CorporationManticore Software
Initial release2019201220132017
Current release29.0.1, April 20245.1, August 20226.0, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache license v2Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoGPL version 2
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 languageJavaC++C++
Server operating systemshostedLinux
OS X
Unix
LinuxFreeBSD
Linux
macOS
Windows
Data schemeschema-freeyes infoschema-less columns are supportedyesFixed schema
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, 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.nononoCan index from XML
Secondary indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL for queryingSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query language
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
Clojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Server-side scripts infoStored proceduresnononouser defined functions
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infomanual/auto, time-basedShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyes, via HDFS, S3 or other storage enginesSource-replica replicationSynchronous replication based on Galera library
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnoACID 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 persistentyesyesyesyes infoThe original contents of fields are not stored in the Manticore index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users and rolesRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users can be defined per databaseno
More information provided by the system vendor
Amazon DocumentDBApache DruidGridDBManticore Search
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 DocumentDBApache DruidGridDBManticore Search
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