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DBMS > GridDB vs. Hypertable vs. Netezza vs. Riak KV

System Properties Comparison GridDB vs. Hypertable vs. Netezza vs. Riak KV

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonHypertable  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonRiak KV  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionScalable in-memory time series database optimized for IoT and Big DataAn open source BigTable implementation based on distributed file systems such as HadoopData warehouse and analytics appliance part of IBM PureSystemsDistributed, fault tolerant key-value store
Primary database modelTime Series DBMSWide column storeRelational DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexes
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score4.01
Rank#79  Overall
#9  Key-value stores
Websitegriddb.netwww.ibm.com/­products/­netezza
Technical documentationdocs.griddb.netwww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperToshiba CorporationHypertable Inc.IBMOpenSource, formerly Basho Technologies
Initial release2013200920002009
Current release5.1, August 20220.9.8.11, March 20163.2.0, December 2022
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoGNU version 3. Commercial license availablecommercialOpen Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++Erlang
Server operating systemsLinuxLinux
OS X
Windows infoan inofficial Windows port is available
Linux infoincluded in applianceLinux
OS X
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampnoyesno
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.nono
Secondary indexesyesrestricted infoonly exact value or prefix value scansyesrestricted
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)noyesno
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
C++ API
Thrift
JDBC
ODBC
OLE DB
HTTP API
Native Erlang Interface
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++
Java
Perl
PHP
Python
Ruby
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
Server-side scripts infoStored proceduresnonoyesErlang
Triggersyesnonoyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factor on file system levelSource-replica replicationselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyesyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelnoACIDno
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 controlAccess rights for users can be defined per databasenoUsers with fine-grained authorization conceptyes, using Riak Security
More information provided by the system vendor
GridDBHypertableNetezza infoAlso called PureData System for Analytics by IBMRiak KV
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» 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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More resources
GridDBHypertableNetezza infoAlso called PureData System for Analytics by IBMRiak KV
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