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DBMS > Dragonfly vs. Google Cloud Datastore vs. Microsoft Access vs. Postgres-XL

System Properties Comparison Dragonfly vs. Google Cloud Datastore vs. Microsoft Access vs. Postgres-XL

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Editorial information provided by DB-Engines
NameDragonfly  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonPostgres-XL  Xexclude from comparison
DescriptionA drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)Based on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelKey-value storeDocument storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.41
Rank#266  Overall
#38  Key-value stores
Score4.47
Rank#76  Overall
#12  Document stores
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Websitegithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
cloud.google.com/­datastorewww.microsoft.com/­en-us/­microsoft-365/­accesswww.postgres-xl.org
Technical documentationwww.dragonflydb.io/­docscloud.google.com/­datastore/­docsdeveloper.microsoft.com/­en-us/­accesswww.postgres-xl.org/­documentation
DeveloperDragonflyDB team and community contributorsGoogleMicrosoft
Initial release2023200819922014 infosince 2012, originally named StormDB
Current release1.0, March 20231902 (16.0.11328.20222), March 201910 R1, October 2018
License infoCommercial or Open SourceOpen Source infoBSL 1.1commercialcommercial infoBundled with Microsoft OfficeOpen Source infoMozilla public license
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++C
Server operating systemsLinuxhostedWindows infoNot a real database server, but making use of DLLsLinux
macOS
Data schemescheme-freeschema-freeyesyes
Typing infopredefined data types such as float or datestrings, hashes, lists, sets, sorted sets, bit arraysyes, details hereyesyes
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.nonoyes infoXML type, but no XML query functionality
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)yes infobut not compliant to any SQL standardyes infodistributed, parallel query execution
APIs and other access methodsProprietary protocol infoRESP - REdis Serialization ProtocolgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
DAO
ODBC
OLE DB
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
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
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresLuausing Google App Engineyes infosince Access 2010 using the ACE-engineuser defined functions
Triggerspublish/subscribe channels provide some trigger functionalityCallbacks using the Google Apps Engineyes infosince Access 2010 using the ACE-engineyes
Partitioning methods infoMethods for storing different data on different nodesShardingnonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication using Paxosnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual 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 integritynoyes infovia ReferenceProperties or Ancestor pathsyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of command blocks and scriptsACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infobut no files for transaction loggingACID infoMVCC
Concurrency infoSupport for concurrent manipulation of datayes, strict serializability by the serveryesyesyes
Durability infoSupport for making data persistentyesyesyes infobut no files for transaction loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlPassword-based authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no infoa simple user-level security was built in till version Access 2003fine grained access rights according to SQL-standard

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More resources
DragonflyGoogle Cloud DatastoreMicrosoft AccessPostgres-XL
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