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DBMS > Apache Druid vs. HarperDB vs. Microsoft Azure Table Storage vs. ObjectBox

System Properties Comparison Apache Druid vs. HarperDB vs. Microsoft Azure Table Storage vs. ObjectBox

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonHarperDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonObjectBox  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataUltra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.A Wide Column Store for rapid development using massive semi-structured datasetsExtremely fast embedded database for small devices, IoT and Mobile
Primary database modelRelational DBMS
Time Series DBMS
Document storeWide column storeObject oriented DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score0.60
Rank#244  Overall
#38  Document stores
Score4.04
Rank#77  Overall
#6  Wide column stores
Score1.29
Rank#166  Overall
#5  Object oriented DBMS
Websitedruid.apache.orgwww.harperdb.ioazure.microsoft.com/­en-us/­services/­storage/­tablesobjectbox.io
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.harperdb.io/­docsdocs.objectbox.io
DeveloperApache Software Foundation and contributorsHarperDBMicrosoftObjectBox Limited
Initial release2012201720122017
Current release29.0.1, April 20243.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infofree community edition availablecommercialOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaNode.jsC and C++
Server operating systemsLinux
OS X
Unix
Linux
OS X
hostedAndroid
iOS
Linux
macOS
Windows
Data schemeyes infoschema-less columns are supporteddynamic schemaschema-freeyes
Typing infopredefined data types such as float or dateyesyes infoJSON data typesyesyes
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.nononono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL for queryingSQL-like data manipulation statementsnono
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
RESTful HTTP APIProprietary native API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
Server-side scripts infoStored proceduresnoCustom Functions infosince release 3.1nono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedA table resides as a whole on one (or more) nodes in a clusterSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyes infothe nodes on which a table resides can be definedyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.online/offline synchronization between client and server
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users and rolesAccess rights based on private key authentication or shared access signaturesyes
More information provided by the system vendor
Apache DruidHarperDBMicrosoft Azure Table StorageObjectBox
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Apache DruidHarperDBMicrosoft Azure Table StorageObjectBox
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