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DBMS > BigObject vs. GridDB vs. Hazelcast vs. Hive

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

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonGridDB  Xexclude from comparisonHazelcast  Xexclude from comparisonHive  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesScalable 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 Hadoop
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedTime Series DBMSKey-value storeRelational 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
Score0.13
Rank#333  Overall
#147  Relational DBMS
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
Websitebigobject.iogriddb.nethazelcast.comhive.apache.org
Technical documentationdocs.bigobject.iodocs.griddb.nethazelcast.org/­imdg/­docscwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperBigObject, Inc.Toshiba CorporationHazelcastApache Software Foundation infoinitially developed by Facebook
Initial release2015201320082012
Current release5.1, August 20225.3.6, November 20233.1.3, April 2022
License infoCommercial or Open Sourcecommercial infofree community edition availableOpen 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 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaJava
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
LinuxAll OS with a Java VMAll OS with a Java VM
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesyes
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.nonoyes infothe object must implement a serialization strategy
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
Thrift
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 proceduresLuanoyes infoEvent Listeners, Executor Servicesyes infouser defined functions and integration of map-reduce
Triggersnoyesyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationyes infoReplicated Mapselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyesyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate consistency within container, eventual consistency across containersImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelone or two-phase-commit; repeatable reads; read commitedno
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyes
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.yesyesyes
User concepts infoAccess controlnoAccess rights for users can be defined per databaseRole-based access controlAccess rights for users, groups and roles
More information provided by the system vendor
BigObjectGridDBHazelcastHive
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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BigObjectGridDBHazelcastHive
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