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DBMS > DolphinDB vs. Dragonfly vs. etcd vs. Sadas Engine vs. Spark SQL

System Properties Comparison DolphinDB vs. Dragonfly vs. etcd vs. Sadas Engine vs. Spark SQL

Editorial information provided by DB-Engines
NameDolphinDB  Xexclude from comparisonDragonfly  Xexclude from comparisonetcd  Xexclude from comparisonSadas Engine  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionDolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceA distributed reliable key-value storeSADAS 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 processing
Primary database modelTime Series DBMSKey-value storeKey-value storeRelational DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.03
Rank#78  Overall
#6  Time Series DBMS
Score0.49
Rank#261  Overall
#38  Key-value stores
Score7.03
Rank#54  Overall
#5  Key-value stores
Score0.07
Rank#373  Overall
#157  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.dolphindb.comgithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
etcd.io
github.com/­etcd-io/­etcd
www.sadasengine.comspark.apache.org/­sql
Technical documentationdocs.dolphindb.cn/­en/­help200/­index.htmlwww.dragonflydb.io/­docsetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
www.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDolphinDB, IncDragonflyDB team and community contributorsSADAS s.r.l.Apache Software Foundation
Initial release2018202320062014
Current releasev2.00.4, January 20221.0, March 20233.4, August 20198.03.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree community version availableOpen Source infoBSL 1.1Open Source infoApache Version 2.0commercial infofree trial version availableOpen Source infoApache 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++GoC++Scala
Server operating systemsLinux
Windows
LinuxFreeBSD
Linux
Windows infoexperimental
AIX
Linux
Windows
Linux
OS X
Windows
Data schemeyesscheme-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesstrings, hashes, lists, sets, sorted sets, bit arraysnoyesyes
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 indexesyesnonoyesno
SQL infoSupport of SQLSQL-like query languagenonoyesSQL-like DML and DDL statements
APIs and other access methodsJDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
Proprietary protocol infoRESP - REdis Serialization ProtocolgRPC
JSON over HTTP
JDBC
ODBC
Proprietary protocol
JDBC
ODBC
Supported programming languagesC#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
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
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
.Net
C
C#
C++
Groovy
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesLuanonono
Triggersnopublish/subscribe channels provide some trigger functionalityyes, watching key changesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioninghorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesAtomic execution of command blocks and scriptsnono
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.yesyesnoyes infomanaged by 'Learn by Usage'no
User concepts infoAccess controlAdministrators, Users, GroupsPassword-based authenticationnoAccess rights for users, groups and roles according to SQL-standardno

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More resources
DolphinDBDragonflyetcdSadas EngineSpark SQL
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