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DBMS > Apache Druid vs. Hazelcast vs. Hive vs. Microsoft Azure Table Storage

System Properties Comparison Apache Druid vs. Hazelcast vs. Hive vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonHazelcast  Xexclude from comparisonHive  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA widely adopted in-memory data griddata warehouse software for querying and managing large distributed datasets, built on HadoopA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelRelational DBMS
Time Series DBMS
Key-value storeRelational DBMSWide column store
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Websitedruid.apache.orghazelcast.comhive.apache.orgazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationdruid.apache.org/­docs/­latest/­designhazelcast.org/­imdg/­docscwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperApache Software Foundation and contributorsHazelcastApache Software Foundation infoinitially developed by FacebookMicrosoft
Initial release2012200820122012
Current release29.0.1, April 20245.3.6, November 20233.1.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2; commercial licenses availableOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJava
Server operating systemsLinux
OS X
Unix
All OS with a Java VMAll OS with a Java VMhosted
Data schemeyes infoschema-less columns are supportedschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes
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
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL for queryingSQL-like query languageSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
Thrift
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++
Java
PHP
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoyes infoEvent Listeners, Executor Servicesyes infouser defined functions and integration of map-reduceno
Triggersnoyes infoEventsnono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyes infoReplicated Mapselectable replication factoryes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoone or two-phase-commit; repeatable reads; read commitednooptimistic locking
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.noyesno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemRole-based access controlAccess rights for users, groups and rolesAccess rights based on private key authentication or shared access signatures

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More resources
Apache DruidHazelcastHiveMicrosoft Azure Table Storage
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