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DBMS > Amazon Neptune vs. Dragonfly vs. etcd vs. Sadas Engine vs. Spark SQL

System Properties Comparison Amazon Neptune vs. Dragonfly vs. etcd vs. Sadas Engine vs. Spark SQL

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonDragonfly  Xexclude from comparisonetcd  Xexclude from comparisonSadas Engine  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudA 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 modelGraph DBMS
RDF store
Key-value storeKey-value storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
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
Websiteaws.amazon.com/­neptunegithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
etcd.io
github.com/­etcd-io/­etcd
www.sadasengine.comspark.apache.org/­sql
Technical documentationaws.amazon.com/­neptune/­developer-resourceswww.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
DeveloperAmazonDragonflyDB team and community contributorsSADAS s.r.l.Apache Software Foundation
Initial release2017202320062014
Current release1.0, March 20233.4, August 20198.03.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen 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 serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++GoC++Scala
Server operating systemshostedLinuxFreeBSD
Linux
Windows infoexperimental
AIX
Linux
Windows
Linux
OS X
Windows
Data schemeschema-freescheme-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 indexesnononoyesno
SQL infoSupport of SQLnononoyesSQL-like DML and DDL statements
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
Proprietary protocol infoRESP - REdis Serialization ProtocolgRPC
JSON over HTTP
JDBC
ODBC
Proprietary protocol
JDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
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 proceduresnoLuanonono
Triggersnopublish/subscribe channels provide some trigger functionalityyes, watching key changesnono
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.Source-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 methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of command blocks and scriptsnono
Concurrency infoSupport for concurrent manipulation of datayesyes, strict serializability by the serveryesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infomanaged by 'Learn by Usage'no
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Password-based authenticationnoAccess rights for users, groups and roles according to SQL-standardno

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More resources
Amazon NeptuneDragonflyetcdSadas EngineSpark SQL
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