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DBMS > etcd vs. Faircom DB vs. Realm vs. Spark SQL vs. STSdb

System Properties Comparison etcd vs. Faircom DB vs. Realm vs. Spark SQL vs. STSdb

Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonRealm  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionA distributed reliable key-value storeNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataSpark SQL is a component on top of 'Spark Core' for structured data processingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelKey-value storeKey-value store
Relational DBMS
Document storeRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.25
Rank#54  Overall
#5  Key-value stores
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score7.60
Rank#52  Overall
#9  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Websiteetcd.io
github.com/­etcd-io/­etcd
www.faircom.com/­products/­faircom-dbrealm.iospark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlrealm.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFairCom CorporationRealm, acquired by MongoDB in May 2019Apache Software FoundationSTS Soft SC
Initial release1979201420142011
Current release3.4, August 2019V12, November 20203.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoRestricted, free version availableOpen SourceOpen Source infoApache 2.0Open Source infoGPLv2, commercial license available
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 languageGoANSI C, C++ScalaC#
Server operating systemsFreeBSD
Linux
Windows infoexperimental
AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Android
Backend: server-less
iOS
Windows
Linux
OS X
Windows
Windows
Data schemeschema-freeschema free, schema optional, schema required, partial schema,yesyesyes
Typing infopredefined data types such as float or datenoyes, ANSI SQL Types, JSON, typed binary structuresyesyesyes infoprimitive types and user defined types (classes)
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.nononono
Secondary indexesnoyesyesnono
SQL infoSupport of SQLnoyes, ANSI SQL with proprietary extensionsnoSQL-like DML and DDL statementsno
APIs and other access methodsgRPC
JSON over HTTP
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
JDBC
ODBC
.NET Client API
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
.Net
Java infowith Android only
Objective-C
React Native
Swift
Java
Python
R
Scala
C#
Java
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++no inforuns within the applications so server-side scripts are unnecessarynono
Triggersyes, watching key changesyesyes infoChange Listenersnono
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningnoneyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).nonenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanotunable from ACID to Eventually ConsistentACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesYes, tunable from durable to delayed durability to in-memoryyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoIn-Memory realmno
User concepts infoAccess controlnoFine grained access rights according to SQL-standard with additional protections for filesyesnono

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More resources
etcdFaircom DB infoformerly c-treeACERealmSpark SQLSTSdb
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