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DBMS > etcd vs. GridDB vs. IBM Db2 warehouse vs. InterSystems IRIS vs. Spark SQL

System Properties Comparison etcd vs. GridDB vs. IBM Db2 warehouse vs. InterSystems IRIS vs. Spark SQL

Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonGridDB  Xexclude from comparisonIBM Db2 warehouse infoformerly named IBM dashDB  Xexclude from comparisonInterSystems IRIS  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA distributed reliable key-value storeScalable in-memory time series database optimized for IoT and Big DataCloud-based data warehousing serviceA containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalabilitySpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeTime Series DBMSRelational DBMSDocument store
Key-value store
Object oriented DBMS
Relational DBMS
Relational DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.03
Rank#54  Overall
#5  Key-value stores
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score1.37
Rank#160  Overall
#74  Relational DBMS
Score3.54
Rank#84  Overall
#14  Document stores
#10  Key-value stores
#1  Object oriented DBMS
#45  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
griddb.netwww.ibm.com/­products/­db2/­warehousewww.intersystems.com/­products/­intersystems-irisspark.apache.org/­sql
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.griddb.netdocs.intersystems.com/­irislatest/­csp/­docbook/­DocBook.UI.Page.clsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperToshiba CorporationIBMInterSystemsApache Software Foundation
Initial release2013201420182014
Current release3.4, August 20195.1, August 20222023.3, June 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++Scala
Server operating systemsFreeBSD
Linux
Windows infoexperimental
LinuxhostedAIX
Linux
macOS
Ubuntu
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyesdepending on used data modelyes
Typing infopredefined data types such as float or datenoyes infonumerical, string, blob, geometry, boolean, timestampyesyesyes
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 infoImport/export of XML data possibleyesno
Secondary indexesnoyesyesyesno
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)yesyesSQL-like DML and DDL statements
APIs and other access methodsgRPC
JSON over HTTP
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
.NET Client API
JDBC
ODBC
OLE DB
JDBC
ODBC
RESTful HTTP API
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
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
.Net
C++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonoPL/SQL, SQL PLyesno
Triggersyes, watching key changesyesyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes, 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.Source-replica replicationyesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelACIDACIDno
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.noyesyesyesno
User concepts infoAccess controlnoAccess rights for users can be defined per databasefine grained access rights according to SQL-standardyesno
More information provided by the system vendor
etcdGridDBIBM Db2 warehouse infoformerly named IBM dashDBInterSystems IRISSpark SQL
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
InterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
etcdGridDBIBM Db2 warehouse infoformerly named IBM dashDBInterSystems IRISSpark SQL
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