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DBMS > Hazelcast vs. HBase vs. Hive vs. LevelDB

System Properties Comparison Hazelcast vs. HBase vs. Hive vs. LevelDB

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Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonHBase  Xexclude from comparisonHive  Xexclude from comparisonLevelDB  Xexclude from comparison
DescriptionA widely adopted in-memory data gridWide-column store based on Apache Hadoop and on concepts of BigTabledata warehouse software for querying and managing large distributed datasets, built on HadoopEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string values
Primary database modelKey-value storeWide column storeRelational DBMSKey-value store
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.46
Rank#61  Overall
#7  Key-value stores
Score27.97
Rank#26  Overall
#2  Wide column stores
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score2.25
Rank#115  Overall
#19  Key-value stores
Websitehazelcast.comhbase.apache.orghive.apache.orggithub.com/­google/­leveldb
Technical documentationhazelcast.org/­imdg/­docshbase.apache.org/­book.htmlcwiki.apache.org/­confluence/­display/­Hive/­Homegithub.com/­google/­leveldb/­blob/­main/­doc/­index.md
DeveloperHazelcastApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software Foundation infoinitially developed by FacebookGoogle
Initial release2008200820122011
Current release5.3.6, November 20232.3.4, January 20213.1.3, April 20221.23, February 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache version 2Open Source infoApache Version 2Open Source infoBSD
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJavaC++
Server operating systemsAll OS with a Java VMLinux
Unix
Windows infousing Cygwin
All OS with a Java VMIllumos
Linux
OS X
Windows
Data schemeschema-freeschema-free, schema definition possibleyesschema-free
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyesno
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.yes infothe object must implement a serialization strategynono
Secondary indexesyesnoyesno
SQL infoSupport of SQLSQL-like query languagenoSQL-like DML and DDL statementsno
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
JDBC
ODBC
Thrift
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Java
PHP
Python
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor Servicesyes infoCoprocessors in Javayes infouser defined functions and integration of map-reduceno
Triggersyes infoEventsyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated MapMulti-source replication
Source-replica replication
selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency or Eventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitedSingle row ACID (across millions of columns)nono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infowith automatic compression on writes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlRole-based access controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights for users, groups and rolesno

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HazelcastHBaseHiveLevelDB
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