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DBMS > GridGain vs. Microsoft Azure Table Storage vs. Riak KV vs. Sadas Engine

System Properties Comparison GridGain vs. Microsoft Azure Table Storage vs. Riak KV vs. Sadas Engine

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Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonRiak KV  Xexclude from comparisonSadas Engine  Xexclude from comparison
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteA Wide Column Store for rapid development using massive semi-structured datasetsDistributed, fault tolerant key-value storeSADAS Engine is a columnar DBMS specifically designed for high performance in Data warehouse environments
Primary database modelKey-value store
Relational DBMS
Wide column storeKey-value store infowith links between data sets and object tags for the creation of secondary indexesRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.67
Rank#133  Overall
#24  Key-value stores
#66  Relational DBMS
Score5.25
Rank#71  Overall
#5  Wide column stores
Score5.88
Rank#63  Overall
#8  Key-value stores
Score0.00
Rank#351  Overall
#146  Relational DBMS
Websitewww.gridgain.comazure.microsoft.com/­en-us/­services/­storage/­tablesriak.com/­products/­riak-kvwww.sadasengine.com
Technical documentationwww.gridgain.com/­docs/­latestwww.sadasengine.com/­index.php/­downloads/­documentation-columnar-db
DeveloperGridGain Systems, Inc.MicrosoftBasho TechnologiesSADAS s.r.l.
Initial release2007201220092006
Current releaseGridGain 8.5.12.1.0, April 20158.0
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache version 2, commercial enterprise editioncommercial infofree trial version available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetErlangC++
Server operating systemsLinux
OS X
Solaris
Windows
hostedLinux
OS X
AIX
Linux
Windows
Data schemeyesschema-freeschema-freeyes
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.yesnonono
Secondary indexesyesnorestrictedyes
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLnonoyes
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
RESTful HTTP APIHTTP API
Native Erlang Interface
JDBC
ODBC
Proprietary protocol
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
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
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)noJavaScript and Erlangno
Triggersyes (cache interceptors and events)noyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceSharding infono "single point of failure"horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)noyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono infolinks between data sets can be storedyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic lockingno
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.yesnoyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlSecurity Hooks for custom implementationsAccess rights based on private key authentication or shared access signaturesnoAccess rights for users, groups and roles according to SQL-standard

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More resources
GridGainMicrosoft Azure Table StorageRiak KVSadas Engine
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