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DBMS > GigaSpaces vs. Netezza vs. Riak KV vs. Sqrrl

System Properties Comparison GigaSpaces vs. Netezza vs. Riak KV vs. Sqrrl

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Editorial information provided by DB-Engines
NameGigaSpaces  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  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.
DescriptionHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsData warehouse and analytics appliance part of IBM PureSystemsDistributed, fault tolerant key-value storeAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelDocument store
Object oriented DBMS infoValues are user defined objects
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 modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Websitewww.gigaspaces.comwww.ibm.com/­products/­netezzasqrrl.com
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmlwww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperGigaspaces TechnologiesIBMOpenSource, formerly Basho TechnologiesAmazon infooriginally Sqrrl Data, Inc.
Initial release2000200020092012
Current release15.5, September 20203.2.0, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial licenses availablecommercialOpen 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++, .NetErlangJava
Server operating systemsLinux
macOS
Solaris
Windows
Linux infoincluded in applianceLinux
OS X
Linux
Data schemeschema-freeyesschema-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.no infoXML can be used for describing objects metadatano
Secondary indexesyesyesrestrictedyes
SQL infoSupport of SQLSQL-99 for query and DML statementsyesnono
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
ODBC
OLE DB
HTTP API
Native Erlang Interface
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languages.Net
C++
Java
Python
Scala
C
C++
Fortran
Java
Lua
Perl
Python
R
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 proceduresyesyesErlangno
Triggersyes, event driven architecturenoyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infono "single point of failure"Sharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Source-replica replicationselectable replication factorselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsyesyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYEventual ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynonono 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 controlRole-based access controlUsers with fine-grained authorization conceptyes, using Riak SecurityCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
GigaSpacesNetezza infoAlso called PureData System for Analytics by IBMRiak KVSqrrl
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