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

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

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonHazelcast  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 gridA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelRelational DBMS
Time Series DBMS
Key-value storeWide 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
Score3.33
Rank#99  Overall
#51  Relational DBMS
#7  Time Series DBMS
Score7.66
Rank#54  Overall
#5  Key-value stores
Score5.35
Rank#71  Overall
#6  Wide column stores
Websitedruid.apache.orghazelcast.comazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationdruid.apache.org/­docs/­latest/­designhazelcast.org/­imdg/­docs
DeveloperApache Software Foundation and contributorsHazelcastMicrosoft
Initial release201220082012
Current release29.0.0, February 20245.3.6, November 2023
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2; commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud servicenonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava
Server operating systemsLinux
OS X
Unix
All OS with a Java VMhosted
Data schemeyes infoschema-less columns are supportedschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes
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 indexesyesyesno
SQL infoSupport of SQLSQL for queryingSQL-like query languageno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JCache
JPA
Memcached protocol
RESTful HTTP API
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoyes infoEvent Listeners, Executor Servicesno
Triggersnoyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyes infoReplicated Mapyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoone or two-phase-commit; repeatable reads; read commitedoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
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 based on private key authentication or shared access signatures

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More resources
Apache DruidHazelcastMicrosoft Azure Table Storage
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