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DBMS > Amazon DocumentDB vs. Manticore Search vs. ObjectBox vs. Tkrzw

System Properties Comparison Amazon DocumentDB vs. Manticore Search vs. ObjectBox vs. Tkrzw

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonManticore Search  Xexclude from comparisonObjectBox  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceMulti-storage database for search, including full-text search.Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectorsA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelDocument storeSearch engineObject oriented DBMS
Vector DBMS
Key-value store
Secondary database modelsTime Series DBMS infousing the Manticore Columnar LibraryTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score0.29
Rank#302  Overall
#21  Search engines
Score1.29
Rank#166  Overall
#5  Object oriented DBMS
#7  Vector DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websiteaws.amazon.com/­documentdbmanticoresearch.comgithub.com/­objectbox
objectbox.io
dbmx.net/­tkrzw
Technical documentationaws.amazon.com/­documentdb/­resourcesmanual.manticoresearch.comdocs.objectbox.io
DeveloperManticore SoftwareObjectBox LimitedMikio Hirabayashi
Initial release2019201720172020
Current release6.0, February 20234.0 (May 2024)0.9.3, August 2020
License infoCommercial or Open SourcecommercialOpen Source infoGPL version 2Bindings are released under Apache 2.0 infoApache License 2.0Open 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 and C++C++
Server operating systemshostedFreeBSD
Linux
macOS
Windows
Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows
Linux
macOS
Data schemeschema-freeFixed schemayesschema-free
Typing infopredefined data types such as float or dateyesInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyes, plus "flex" map-like typesno
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.noCan index from XMLnono
Secondary indexesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoSQL-like query languagenono
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Proprietary native API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnouser defined functionsnono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoPartitioning is done manually, search queries against distributed index is supportednonenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasSynchronous replication based on Galera libraryData sync between devices allowing occasional connected databases to work completely offlinenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsyes infoisolated transactions for atomic changes and binary logging for safe writesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoThe original contents of fields are not stored in the Manticore index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infousing specific database classes
User concepts infoAccess controlAccess rights for users and rolesnoyesno
More information provided by the system vendor
Amazon DocumentDBManticore SearchObjectBoxTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
News

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29 May 2024

Vector search: making sense of search queries
29 May 2024

Python on-device Vector and Object Database for Local AI
28 May 2024

Evolution of search: traditional vs vector search
23 May 2024

On-device Vector Database for Dart/Flutter
21 May 2024

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More resources
Amazon DocumentDBManticore SearchObjectBoxTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
Recent citations in the news

A hybrid approach for homogeneous migration to an Amazon DocumentDB elastic cluster | Amazon Web Services
4 June 2024, AWS Blog

Vector search for Amazon DocumentDB (with MongoDB compatibility) is now generally available | Amazon Web Services
29 November 2023, AWS Blog

Use LangChain and vector search on Amazon DocumentDB to build a generative AI chatbot | Amazon Web Services
20 May 2024, AWS Blog

Use headless clusters in Amazon DocumentDB for cost-effective multi-Region resiliency | Amazon Web Services
8 March 2024, AWS Blog

Reduce cost and improve performance by migrating to Amazon DocumentDB 5.0 | Amazon Web Services
15 April 2024, AWS Blog

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4 December 2018, FinSMEs

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