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

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

Editorial information provided by DB-Engines
NameDragonfly  Xexclude from comparisonetcd  Xexclude from comparisonHarperDB  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 storeUltra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.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 processing
Primary database modelKey-value storeKey-value storeDocument storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.41
Rank#266  Overall
#38  Key-value stores
Score7.25
Rank#54  Overall
#5  Key-value stores
Score0.55
Rank#248  Overall
#38  Document stores
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
etcd.io
github.com/­etcd-io/­etcd
www.harperdb.iowww.sadasengine.comspark.apache.org/­sql
Technical documentationwww.dragonflydb.io/­docsetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.harperdb.io/­docswww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDragonflyDB team and community contributorsHarperDBSADAS s.r.l.Apache Software Foundation
Initial release2023201720062014
Current release1.0, March 20233.4, August 20193.1, August 20218.03.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoBSL 1.1Open Source infoApache Version 2.0commercial infofree community edition availablecommercial 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++GoNode.jsC++Scala
Server operating systemsLinuxFreeBSD
Linux
Windows infoexperimental
Linux
OS X
AIX
Linux
Windows
Linux
OS X
Windows
Data schemescheme-freeschema-freedynamic schemayesyes
Typing infopredefined data types such as float or datestrings, hashes, lists, sets, sorted sets, bit arraysnoyes infoJSON data typesyesyes
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 indexesnonoyesyesno
SQL infoSupport of SQLnonoSQL-like data manipulation statementsyesSQL-like DML and DDL statements
APIs and other access methodsProprietary protocol infoRESP - REdis Serialization ProtocolgRPC
JSON over HTTP
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
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
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
.Net
C
C#
C++
Groovy
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresLuanoCustom Functions infosince release 3.1nono
Triggerspublish/subscribe channels provide some trigger functionalityyes, watching key changesnonono
Partitioning methods infoMethods for storing different data on different nodesA table resides as a whole on one (or more) nodes in a clusterhorizontal 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.yes infothe nodes on which a table resides can be definednonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of command blocks and scriptsnoAtomic execution of specific operationsno
Concurrency infoSupport for concurrent manipulation of datayes, strict serializability by the serveryesyesyesyes
Durability infoSupport for making data persistentyesyesyes, using LMDByesyes
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 for users and rolesAccess rights for users, groups and roles according to SQL-standardno

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More resources
DragonflyetcdHarperDBSadas EngineSpark SQL
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