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DBMS > Apache Druid vs. GeoSpock vs. Hypertable vs. openGauss

System Properties Comparison Apache Druid vs. GeoSpock vs. Hypertable vs. openGauss

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGeoSpock  Xexclude from comparisonHypertable  Xexclude from comparisonopenGauss  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.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 dataSpatial and temporal data processing engine for extreme data scaleAn open source BigTable implementation based on distributed file systems such as HadoopAn enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSWide column storeRelational DBMS
Secondary database modelsTime Series DBMSDocument store
Spatial 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
Score1.06
Rank#184  Overall
#84  Relational DBMS
Websitedruid.apache.orggeospock.comgitee.com/­opengauss
opengauss.org
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.opengauss.org/­en
gitee.com/­opengauss/­docs
DeveloperApache Software Foundation and contributorsGeoSpockHypertable Inc.Huawei and openGauss community
Initial release201220092019
Current release29.0.1, April 20242.0, September 20190.9.8.11, March 20163.0, March 2022
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoGNU version 3. Commercial license availableOpen Source
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, JavascriptC++C, C++, Java
Server operating systemsLinux
OS X
Unix
hostedLinux
OS X
Windows infoan inofficial Windows port is available
Linux
Data schemeyes infoschema-less columns are supportedyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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 indexesyestemporal, categoricalrestricted infoonly exact value or prefix value scansyes
SQL infoSupport of SQLSQL for queryingANSI SQL for query only (using Presto)noANSI SQL 2011
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBCC++ API
Thrift
JDBC
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C++
Java
Perl
PHP
Python
Ruby
C
C++
Java
Server-side scripts infoStored proceduresnononoyes
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedAutomatic shardingShardinghorizontal partitioning (by range, list and hash)
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication factor on file system levelSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
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 datanononoACID
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.nonono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users can be defined per tablenoAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache DruidGeoSpockHypertableopenGauss
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