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DBMS > Dragonfly vs. etcd vs. Google Cloud Spanner vs. Sadas Engine vs. Spark SQL

System Properties Comparison Dragonfly vs. etcd vs. Google Cloud Spanner vs. Sadas Engine vs. Spark SQL

Editorial information provided by DB-Engines
NameDragonfly  Xexclude from comparisonetcd  Xexclude from comparisonGoogle Cloud Spanner  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 storeA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.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 storeRelational DBMSRelational 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
Score2.84
Rank#100  Overall
#51  Relational DBMS
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
cloud.google.com/­spannerwww.sadasengine.comspark.apache.org/­sql
Technical documentationwww.dragonflydb.io/­docsetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
cloud.google.com/­spanner/­docswww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDragonflyDB team and community contributorsGoogleSADAS s.r.l.Apache Software Foundation
Initial release2023201720062014
Current release1.0, March 20233.4, August 20198.03.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoBSL 1.1Open Source infoApache Version 2.0commercialcommercial infofree trial version availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++GoC++Scala
Server operating systemsLinuxFreeBSD
Linux
Windows infoexperimental
hostedAIX
Linux
Windows
Linux
OS X
Windows
Data schemescheme-freeschema-freeyesyesyes
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 indexesnonoyesyesno
SQL infoSupport of SQLnonoyes infoQuery statements complying to ANSI 2011yesSQL-like DML and DDL statements
APIs and other access methodsProprietary protocol infoRESP - REdis Serialization ProtocolgRPC
JSON over HTTP
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
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
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Groovy
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresLuanononono
Triggerspublish/subscribe channels provide some trigger functionalityyes, watching key changesnonono
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 replication with 3 replicas for regional instances.nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of command blocks and scriptsnoACID infoStrict serializable isolationno
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.yesnonoyes infomanaged by 'Learn by Usage'no
User concepts infoAccess controlPassword-based authenticationnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles according to SQL-standardno

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More resources
DragonflyetcdGoogle Cloud SpannerSadas EngineSpark SQL
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