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DBMS > GridDB vs. Hazelcast vs. Hive vs. Ingres

System Properties Comparison GridDB vs. Hazelcast vs. Hive vs. Ingres

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonHazelcast  Xexclude from comparisonHive  Xexclude from comparisonIngres  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataA widely adopted in-memory data griddata warehouse software for querying and managing large distributed datasets, built on HadoopWell established RDBMS
Primary database modelTime Series DBMSKey-value storeRelational DBMSRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
Document store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score4.11
Rank#81  Overall
#44  Relational DBMS
Websitegriddb.nethazelcast.comhive.apache.orgwww.actian.com/­databases/­ingres
Technical documentationdocs.griddb.nethazelcast.org/­imdg/­docscwiki.apache.org/­confluence/­display/­Hive/­Homedocs.actian.com/­ingres
DeveloperToshiba CorporationHazelcastApache Software Foundation infoinitially developed by FacebookActian Corporation
Initial release2013200820121974 infooriginally developed at University Berkely in early 1970s
Current release5.1, August 20225.3.6, November 20233.1.3, April 202211.2, May 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 infoApache Version 2; commercial licenses availableOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaJavaC
Server operating systemsLinuxAll OS with a Java VMAll OS with a Java VMAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesyesyes
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.noyes infothe object must implement a serialization strategyno infobut tools for importing/exporting data from/to XML-files available
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query languageSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
Thrift
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++
Java
PHP
Python
Server-side scripts infoStored proceduresnoyes infoEvent Listeners, Executor Servicesyes infouser defined functions and integration of map-reduceyes
Triggersyesyes infoEventsnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneously
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoReplicated Mapselectable replication factorIngres Replicator
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyesyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelone or two-phase-commit; repeatable reads; read commitednoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoMVCC
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.yesyesno
User concepts infoAccess controlAccess rights for users can be defined per databaseRole-based access controlAccess rights for users, groups and rolesfine grained access rights according to SQL-standard
More information provided by the system vendor
GridDBHazelcastHiveIngres
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
GridDBHazelcastHiveIngres
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