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DBMS > Amazon DocumentDB vs. Dragonfly vs. EsgynDB vs. Google Cloud Datastore vs. Sadas Engine

System Properties Comparison Amazon DocumentDB vs. Dragonfly vs. EsgynDB vs. Google Cloud Datastore vs. Sadas Engine

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonDragonfly  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonSadas Engine  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceA drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments
Primary database modelDocument storeKey-value storeRelational DBMSDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#124  Overall
#22  Document stores
Score0.44
Rank#255  Overall
#38  Key-value stores
Score0.15
Rank#325  Overall
#144  Relational DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Score0.00
Rank#385  Overall
#159  Relational DBMS
Websiteaws.amazon.com/­documentdbgithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
www.esgyn.cncloud.google.com/­datastorewww.sadasengine.com
Technical documentationaws.amazon.com/­documentdb/­resourceswww.dragonflydb.io/­docscloud.google.com/­datastore/­docswww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperDragonflyDB team and community contributorsEsgynGoogleSADAS s.r.l.
Initial release20192023201520082006
Current release1.0, March 20238.0
License infoCommercial or Open SourcecommercialOpen Source infoBSL 1.1commercialcommercialcommercial infofree trial version available
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++, JavaC++
Server operating systemshostedLinuxLinuxhostedAIX
Linux
Windows
Data schemeschema-freescheme-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesstrings, hashes, lists, sets, sorted sets, bit arraysyesyes, details hereyes
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.nonononono
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLnonoyesSQL-like query language (GQL)yes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)Proprietary protocol infoRESP - REdis Serialization ProtocolADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
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
All languages supporting JDBC/ODBC/ADO.Net.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-side scripts infoStored proceduresnoLuaJava Stored Proceduresusing Google App Engineno
Triggersnopublish/subscribe channels provide some trigger functionalitynoCallbacks using the Google Apps Engineno
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 replicasSource-replica replicationMulti-source replication between multi datacentersMulti-source replication using Paxosnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noyesyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenoyesyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsAtomic execution of command blocks and scriptsACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
Concurrency infoSupport for concurrent manipulation of datayesyes, strict serializability by the serveryesyesyes
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.yesnonoyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlAccess rights for users and rolesPassword-based authenticationfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles according to SQL-standard

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More resources
Amazon DocumentDBDragonflyEsgynDBGoogle Cloud DatastoreSadas Engine
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