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DBMS > Amazon Redshift vs. IRONdb vs. Kingbase vs. Realm vs. Splice Machine

System Properties Comparison Amazon Redshift vs. IRONdb vs. Kingbase vs. Realm vs. Splice Machine

Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonIRONdb  Xexclude from comparisonKingbase  Xexclude from comparisonRealm  Xexclude from comparisonSplice Machine  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionLarge scale data warehouse service for use with business intelligence toolsA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityAn enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSTime Series DBMSRelational DBMSDocument storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score17.94
Rank#34  Overall
#21  Relational DBMS
Score0.45
Rank#262  Overall
#123  Relational DBMS
Score7.60
Rank#52  Overall
#9  Document stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteaws.amazon.com/­redshiftwww.circonus.com/solutions/time-series-database/www.kingbase.com.cnrealm.iosplicemachine.com
Technical documentationdocs.aws.amazon.com/­redshiftdocs.circonus.com/irondb/category/getting-startedrealm.io/­docssplicemachine.com/­how-it-works
DeveloperAmazon (based on PostgreSQL)Circonus LLC.BeiJing KINGBASE Information technologies inc.Realm, acquired by MongoDB in May 2019Splice Machine
Initial release20122017199920142014
Current releaseV0.10.20, January 2018V8.0, August 20213.1, March 2021
License infoCommercial or Open SourcecommercialcommercialcommercialOpen SourceOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC and C++C and JavaJava
Server operating systemshostedLinuxLinux
Windows
Android
Backend: server-less
iOS
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyesyesyes
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 indexesrestrictednoyesyesyes
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardSQL-like query language (Circonus Analytics Query Language: CAQL)Standard with numerous extensionsnoyes
APIs and other access methodsJDBC
ODBC
HTTP APIADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT
JDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
.Net
Java infowith Android only
Objective-C
React Native
Swift
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions infoin Pythonyes, in Luauser defined functionsno inforuns within the applications so server-side scripts are unnecessaryyes infoJava
Triggersnonoyesyes infoChange Listenersyes
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodehorizontal partitioning (by range, list and hash) and vertical partitioningnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesconfigurable replication factor, datacenter awareyesnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemnoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
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.yesnoyes infoIn-Memory realmyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standardyesAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon RedshiftIRONdbKingbaseRealmSplice Machine
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