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DBMS > DataFS vs. etcd vs. InfinityDB vs. Sadas Engine vs. Spark SQL

System Properties Comparison DataFS vs. etcd vs. InfinityDB vs. Sadas Engine vs. Spark SQL

Editorial information provided by DB-Engines
NameDataFS  Xexclude from comparisonetcd  Xexclude from comparisonInfinityDB  Xexclude from comparisonSadas Engine  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAll data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.A distributed reliable key-value storeA Java embedded Key-Value Store which extends the Java Map interfaceSADAS 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 modelObject oriented DBMSKey-value storeKey-value storeRelational DBMSRelational DBMS
Secondary database modelsGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.06
Rank#354  Overall
#15  Object oriented DBMS
Score7.25
Rank#54  Overall
#5  Key-value stores
Score0.00
Rank#378  Overall
#57  Key-value stores
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitenewdatabase.cometcd.io
github.com/­etcd-io/­etcd
boilerbay.comwww.sadasengine.comspark.apache.org/­sql
Technical documentationdev.mobiland.com/­Overview.xspetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
boilerbay.com/­infinitydb/­manualwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMobiland AGBoiler Bay Inc.SADAS s.r.l.Apache Software Foundation
Initial release2018200220062014
Current release1.1.263, October 20223.4, August 20194.08.03.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialcommercial 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 languageGoJavaC++Scala
Server operating systemsWindowsFreeBSD
Linux
Windows infoexperimental
All OS with a Java VMAIX
Linux
Windows
Linux
OS X
Windows
Data schemeClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)schema-freeyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyesyes
Typing infopredefined data types such as float or dateyesnoyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyesyes
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 indexesnonono infomanual creation possible, using inversions based on multi-value capabilityyesno
SQL infoSupport of SQLnononoyesSQL-like DML and DDL statements
APIs and other access methods.NET Client API
Proprietary client DLL
WinRT client
gRPC
JSON over HTTP
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
JDBC
ODBC
Proprietary protocol
JDBC
ODBC
Supported programming languages.Net
C
C#
C++
VB.Net
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
Java.Net
C
C#
C++
Groovy
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnononono
Triggersno, except callback-events from server when changes happenedyes, watching key changesnonono
Partitioning methods infoMethods for storing different data on different nodesProprietary Sharding systemnonehorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.nonenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate Consistency
Foreign keys infoReferential integrityyesnono infomanual creation possible, using inversions based on multi-value capabilityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoOptimistic locking for transactions; no isolation for bulk loadsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.nononoyes infomanaged by 'Learn by Usage'no
User concepts infoAccess controlWindows-ProfilenonoAccess rights for users, groups and roles according to SQL-standardno

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More resources
DataFSetcdInfinityDBSadas EngineSpark SQL
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