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

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

Editorial information provided by DB-Engines
NameDragonfly  Xexclude from comparisonetcd  Xexclude from comparisonGeode  Xexclude from comparisonSadas Engine  Xexclude from comparisonSpark SQL  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 instanceA distributed reliable key-value storeGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesSADAS 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 modelKey-value storeKey-value storeKey-value storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.49
Rank#261  Overall
#38  Key-value stores
Score7.03
Rank#54  Overall
#5  Key-value stores
Score1.86
Rank#134  Overall
#24  Key-value stores
Score0.07
Rank#373  Overall
#157  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
etcd.io
github.com/­etcd-io/­etcd
geode.apache.orgwww.sadasengine.comspark.apache.org/­sql
Technical documentationwww.dragonflydb.io/­docsetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
geode.apache.org/­docswww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDragonflyDB team and community contributorsOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.SADAS s.r.l.Apache Software Foundation
Initial release2023200220062014
Current release1.0, March 20233.4, August 20191.1, February 20178.03.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoBSL 1.1Open Source infoApache Version 2.0Open Source infoApache Version 2; commercial licenses available as Gemfirecommercial 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++GoJavaC++Scala
Server operating systemsLinuxFreeBSD
Linux
Windows infoexperimental
All OS with a Java VM infothe JDK (8 or later) is also requiredAIX
Linux
Windows
Linux
OS X
Windows
Data schemescheme-freeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datestrings, hashes, lists, sets, sorted sets, bit arraysnoyesyesyes
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 indexesnononoyesno
SQL infoSupport of SQLnonoSQL-like query language (OQL)yesSQL-like DML and DDL statements
APIs and other access methodsProprietary protocol infoRESP - REdis Serialization ProtocolgRPC
JSON over HTTP
Java Client API
Memcached protocol
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
JDBC
ODBC
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
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
.Net
All JVM based languages
C++
Groovy
Java
Scala
.Net
C
C#
C++
Groovy
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresLuanouser defined functionsnono
Triggerspublish/subscribe channels provide some trigger functionalityyes, watching key changesyes infoCache Event Listenersnono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of command blocks and scriptsnoyes, on a single nodeno
Concurrency infoSupport for concurrent manipulation of datayes, strict serializability by the serveryesyesyesyes
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.yesnoyesyes infomanaged by 'Learn by Usage'no
User concepts infoAccess controlPassword-based authenticationnoAccess rights per client and object definableAccess rights for users, groups and roles according to SQL-standardno

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More resources
DragonflyetcdGeodeSadas EngineSpark SQL
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