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DBMS > Apache Druid vs. HBase vs. Hypertable vs. Transbase

System Properties Comparison Apache Druid vs. HBase vs. Hypertable vs. Transbase

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonHBase  Xexclude from comparisonHypertable  Xexclude from comparisonTransbase  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataWide-column store based on Apache Hadoop and on concepts of BigTableAn open source BigTable implementation based on distributed file systems such as HadoopA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMS
Time Series DBMS
Wide column storeWide column storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.29
Rank#95  Overall
#49  Relational DBMS
#7  Time Series DBMS
Score31.25
Rank#26  Overall
#2  Wide column stores
Score0.15
Rank#337  Overall
#147  Relational DBMS
Websitedruid.apache.orghbase.apache.orgwww.transaction.de/­en/­products/­transbase.html
Technical documentationdruid.apache.org/­docs/­latest/­designhbase.apache.org/­book.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperApache Software Foundation and contributorsApache Software Foundation infoApache top-level project, originally developed by PowersetHypertable Inc.Transaction Software GmbH
Initial release2012200820091987
Current release29.0.1, April 20242.3.4, January 20210.9.8.11, March 2016Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache version 2Open Source infoGNU version 3. Commercial license availablecommercial infofree development license
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++C and C++
Server operating systemsLinux
OS X
Unix
Linux
Unix
Windows infousing Cygwin
Linux
OS X
Windows infoan inofficial Windows port is available
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyes infoschema-less columns are supportedschema-free, schema definition possibleschema-freeyes
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROnoyes
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.nonono
Secondary indexesyesnorestricted infoonly exact value or prefix value scansyes
SQL infoSupport of SQLSQL for queryingnonoyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
Java API
RESTful HTTP API
Thrift
C++ API
Thrift
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Java
Perl
PHP
Python
Ruby
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresnoyes infoCoprocessors in Javanoyes
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication
Source-replica replication
selectable replication factor on file system levelSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoSingle row ACID (across millions of columns)noyes
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 systemAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnofine grained access rights according to SQL-standard

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More resources
Apache DruidHBaseHypertableTransbase
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