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DBMS > etcd vs. LevelDB vs. Microsoft SQL Server vs. Spark SQL

System Properties Comparison etcd vs. LevelDB vs. Microsoft SQL Server vs. Spark SQL

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Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonLevelDB  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA distributed reliable key-value storeEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesMicrosofts flagship relational DBMSSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeKey-value storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.25
Rank#54  Overall
#5  Key-value stores
Score2.35
Rank#111  Overall
#19  Key-value stores
Score824.29
Rank#3  Overall
#3  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
github.com/­google/­leveldbwww.microsoft.com/­en-us/­sql-serverspark.apache.org/­sql
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
github.com/­google/­leveldb/­blob/­main/­doc/­index.mdlearn.microsoft.com/­en-US/­sql/­sql-serverspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGoogleMicrosoftApache Software Foundation
Initial release201119892014
Current release3.4, August 20191.23, February 2021SQL Server 2022, November 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoBSDcommercial inforestricted free version is availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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SQLServer Flex @ STACKIT offers a managed version of SQL Server with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.
Implementation languageGoC++C++Scala
Server operating systemsFreeBSD
Linux
Windows infoexperimental
Illumos
Linux
OS X
Windows
Linux
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datenonoyesyes
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.nonoyesno
Secondary indexesnonoyesno
SQL infoSupport of SQLnonoyesSQL-like DML and DDL statements
APIs and other access methodsgRPC
JSON over HTTP
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
JDBC
ODBC
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonoTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Javano
Triggersyes, watching key changesnoyesno
Partitioning methods infoMethods for storing different data on different nodesnonetables can be distributed across several files (horizontal partitioning); sharding through federationyes, 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.noneyes, but depending on the SQL-Server Editionnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infowith automatic compression on writesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlnonofine grained access rights according to SQL-standardno

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More resources
etcdLevelDBMicrosoft SQL ServerSpark SQL
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