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

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

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonGridDB  Xexclude from comparisonHarperDB  Xexclude from comparisonManticore Search  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceScalable in-memory time series database optimized for IoT and Big DataHarperDB takes the "stack" out of "tech stack" by combining an ultra-fast document-style data store, in-memory cache, real-time message broker, and your application components into a single distributed technology.Multi-storage database for search, including full-text search.
Primary database modelDocument storeTime Series DBMSDocument storeSearch 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
Score1.91
Rank#124  Overall
#22  Document stores
Score1.91
Rank#123  Overall
#10  Time Series DBMS
Score0.55
Rank#243  Overall
#38  Document stores
Score0.23
Rank#301  Overall
#21  Search engines
Websiteaws.amazon.com/­documentdbgriddb.netwww.harperdb.iomanticoresearch.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.griddb.netdocs.harperdb.io/­docsmanual.manticoresearch.com
DeveloperToshiba CorporationHarperDBManticore Software
Initial release2019201320172017
Current release5.1, August 20223.1, August 20216.0, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial infofree community edition availableOpen Source infoGPL version 2
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Node.jsC++
Server operating systemshostedLinuxLinux
OS X
FreeBSD
Linux
macOS
Windows
Data schemeschema-freeyesdynamic schemaFixed schema
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyes infoJSON data typesInt, 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 SQLnoSQL92, SQL-like TQL (Toshiba Query Language)SQL-like data manipulation statementsSQL-like query language
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Server-side scripts infoStored proceduresnonoCustom Functions infosince release 3.1user defined functions
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingA table resides as a whole on one (or more) nodes in a clusterSharding 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 replicasSource-replica replicationyes infothe nodes on which a table resides can be definedSynchronous replication based on Galera library
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 containersImmediate Consistency
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 operationsACID at container levelAtomic execution of specific operationsyes infoisolated transactions for atomic changes and binary logging for safe writes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes, using LMDByes 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.yesyes
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users can be defined per databaseAccess rights for users and rolesno

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More resources
Amazon DocumentDBGridDBHarperDBManticore Search
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