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DBMS > Amazon DocumentDB vs. Apache Phoenix vs. Dragonfly vs. GridGain vs. Yaacomo

System Properties Comparison Amazon DocumentDB vs. Apache Phoenix vs. Dragonfly vs. GridGain vs. Yaacomo

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache Phoenix  Xexclude from comparisonDragonfly  Xexclude from comparisonGridGain  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceA scale-out RDBMS with evolutionary schema built on Apache HBaseA drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceGridGain is an in-memory computing platform, built on Apache IgniteOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelDocument storeRelational DBMSKey-value storeKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.41
Rank#266  Overall
#38  Key-value stores
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Websiteaws.amazon.com/­documentdbphoenix.apache.orggithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
www.gridgain.comyaacomo.com
Technical documentationaws.amazon.com/­documentdb/­resourcesphoenix.apache.orgwww.dragonflydb.io/­docswww.gridgain.com/­docs/­index.html
DeveloperApache Software FoundationDragonflyDB team and community contributorsGridGain Systems, Inc.Q2WEB GmbH
Initial release20192014202320072009
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20191.0, March 2023GridGain 8.5.1
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoBSL 1.1commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++Java, C++, .Net
Server operating systemshostedLinux
Unix
Windows
LinuxLinux
OS X
Solaris
Windows
Android
Linux
Windows
Data schemeschema-freeyes infolate-bound, schema-on-read capabilitiesscheme-freeyesyes
Typing infopredefined data types such as float or dateyesyesstrings, hashes, lists, sets, sorted sets, bit arraysyesyes
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.nononoyesno
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLnoyesnoANSI-99 for query and DML statements, subset of DDLyes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBCProprietary protocol infoRESP - REdis Serialization ProtocolHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl
C#
C++
Java
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnouser defined functionsLuayes (compute grid and cache interceptors can be used instead)
Triggersnonopublish/subscribe channels provide some trigger functionalityyes (cache interceptors and events)yes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasMulti-source replication
Source-replica replication
Source-replica replicationyes (replicated cache)Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)Hadoop integrationnoyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDAtomic execution of command blocks and scriptsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, strict serializability by the serveryesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes
User concepts infoAccess controlAccess rights for users and rolesAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyPassword-based authenticationSecurity Hooks for custom implementationsfine grained access rights according to SQL-standard

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More resources
Amazon DocumentDBApache PhoenixDragonflyGridGainYaacomo
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