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DBMS > etcd vs. EXASOL vs. Spark SQL

System Properties Comparison etcd vs. EXASOL vs. Spark SQL

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Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonEXASOL  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA distributed reliable key-value storeHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.64
Rank#54  Overall
#5  Key-value stores
Score2.25
Rank#120  Overall
#57  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
www.exasol.comspark.apache.org/­sql
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
www.exasol.com/­resourcesspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperExasolApache Software Foundation
Initial release20002014
Current release3.4, August 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoScala
Server operating systemsFreeBSD
Linux
Windows infoexperimental
Linux
OS X
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or datenoyesyes
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.nonono
Secondary indexesnoyesno
SQL infoSupport of SQLnoyesSQL-like DML and DDL statements
APIs and other access methodsgRPC
JSON over HTTP
.Net
JDBC
ODBC
WebSocket
JDBC
ODBC
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
Java
Lua
Python
R
Java
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functionsno
Triggersyes, watching key changesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingyes, 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.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoHadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlnoAccess rights for users, groups and roles according to SQL-standardno

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More resources
etcdEXASOLSpark SQL
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