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DBMS > GridGain vs. Kingbase vs. Riak KV vs. Sqrrl

System Properties Comparison GridGain vs. Kingbase vs. Riak KV vs. Sqrrl

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Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonKingbase  Xexclude from comparisonRiak KV  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteAn enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.Distributed, fault tolerant key-value storeAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelKey-value store
Relational DBMS
Relational DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexesDocument store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score0.50
Rank#257  Overall
#119  Relational DBMS
Score4.01
Rank#79  Overall
#9  Key-value stores
Websitewww.gridgain.comwww.kingbase.com.cnsqrrl.com
Technical documentationwww.gridgain.com/­docs/­index.htmlwww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperGridGain Systems, Inc.BeiJing KINGBASE Information technologies inc.OpenSource, formerly Basho TechnologiesAmazon infooriginally Sqrrl Data, Inc.
Initial release2007199920092012
Current releaseGridGain 8.5.1V8.0, August 20213.2.0, December 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache version 2, commercial enterprise editioncommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetC and JavaErlangJava
Server operating systemsLinux
OS X
Solaris
Windows
Linux
Windows
Linux
OS X
Linux
Data schemeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesnoyes
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.yesyesno
Secondary indexesyesyesrestrictedyes
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLStandard with numerous extensionsnono
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT
HTTP API
Native Erlang Interface
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)user defined functionsErlangno
Triggersyes (cache interceptors and events)yesyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by range, list and hash) and vertical partitioningSharding infono "single point of failure"Sharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)yesselectable replication factorselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)noyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynoyesno infolinks between data sets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
User concepts infoAccess controlSecurity Hooks for custom implementationsfine grained access rights according to SQL-standardyes, using Riak SecurityCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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