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DBMS > Dragonfly vs. Microsoft Access vs. Sadas Engine vs. Spark SQL vs. VictoriaMetrics

System Properties Comparison Dragonfly vs. Microsoft Access vs. Sadas Engine vs. Spark SQL vs. VictoriaMetrics

Editorial information provided by DB-Engines
NameDragonfly  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonSadas Engine  Xexclude from comparisonSpark SQL  Xexclude from comparisonVictoriaMetrics  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 instanceMicrosoft 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.)SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsSpark SQL is a component on top of 'Spark Core' for structured data processingA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelKey-value storeRelational DBMSRelational DBMSRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.41
Rank#266  Overall
#38  Key-value stores
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score1.32
Rank#162  Overall
#14  Time Series DBMS
Websitegithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
www.microsoft.com/­en-us/­microsoft-365/­accesswww.sadasengine.comspark.apache.org/­sqlvictoriametrics.com
Technical documentationwww.dragonflydb.io/­docsdeveloper.microsoft.com/­en-us/­accesswww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperDragonflyDB team and community contributorsMicrosoftSADAS s.r.l.Apache Software FoundationVictoriaMetrics
Initial release20231992200620142018
Current release1.0, March 20231902 (16.0.11328.20222), March 20198.03.5.0 ( 2.13), September 2023v1.91, May 2023
License infoCommercial or Open SourceOpen Source infoBSL 1.1commercial infoBundled with Microsoft Officecommercial infofree trial version availableOpen Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++C++ScalaGo
Server operating systemsLinuxWindows infoNot a real database server, but making use of DLLsAIX
Linux
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
OpenBSD
Data schemescheme-freeyesyesyes
Typing infopredefined data types such as float or datestrings, hashes, lists, sets, sorted sets, bit arraysyesyesyes
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.nononono
Secondary indexesnoyesyesno
SQL infoSupport of SQLnoyes infobut not compliant to any SQL standardyesSQL-like DML and DDL statementsno
APIs and other access methodsProprietary protocol infoRESP - REdis Serialization ProtocolADO.NET
DAO
ODBC
OLE DB
JDBC
ODBC
Proprietary protocol
JDBC
ODBC
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
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
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
.Net
C
C#
C++
Groovy
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresLuayes infosince Access 2010 using the ACE-enginenonono
Triggerspublish/subscribe channels provide some trigger functionalityyes infosince Access 2010 using the ACE-enginenonono
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnonenonenoneSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of command blocks and scriptsACID infobut no files for transaction loggingnono
Concurrency infoSupport for concurrent manipulation of datayes, strict serializability by the serveryesyesyesyes
Durability infoSupport for making data persistentyesyes infobut no files for transaction loggingyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infomanaged by 'Learn by Usage'nono
User concepts infoAccess controlPassword-based authenticationno infoa simple user-level security was built in till version Access 2003Access rights for users, groups and roles according to SQL-standardno

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More resources
DragonflyMicrosoft AccessSadas EngineSpark SQLVictoriaMetrics
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