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DBMS > Apache Druid vs. Hawkular Metrics vs. MonetDB vs. Spark SQL vs. TerarkDB

System Properties Comparison Apache Druid vs. Hawkular Metrics vs. MonetDB vs. Spark SQL vs. TerarkDB

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonMonetDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTerarkDB  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A relational database management system that stores data in columnsSpark SQL is a component on top of 'Spark Core' for structured data processingA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelRelational DBMS
Time Series DBMS
Time Series DBMSRelational DBMSRelational DBMSKey-value store
Secondary database modelsDocument 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
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score1.72
Rank#141  Overall
#64  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.08
Rank#367  Overall
#56  Key-value stores
Websitedruid.apache.orgwww.hawkular.orgwww.monetdb.orgspark.apache.org/­sqlgithub.com/­bytedance/­terarkdb
Technical documentationdruid.apache.org/­docs/­latest/­designwww.hawkular.org/­hawkular-metrics/­docs/­user-guidewww.monetdb.org/­Documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperApache Software Foundation and contributorsCommunity supported by Red HatMonetDB BVApache Software FoundationByteDance, originally Terark
Initial release20122014200420142016
Current release29.0.1, April 2024Dec2023 (11.49), December 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache 2.0Open Source infoMozilla Public License 2.0Open Source infoApache 2.0commercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaCScalaC++
Server operating systemsLinux
OS X
Unix
Linux
OS X
Windows
FreeBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyes infoschema-less columns are supportedschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyesno
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 indexesyesnoyesnono
SQL infoSupport of SQLSQL for queryingnoyes infoSQL 2003 with some extensionsSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
HTTP RESTJDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
JDBC
ODBC
C++ API
Java API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Go
Java
Python
Ruby
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Java
Python
R
Scala
C++
Java
Server-side scripts infoStored proceduresnonoyes, in SQL, C, Rnono
Triggersnoyes infovia Hawkular Alertingyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedSharding infobased on CassandraSharding via remote tablesyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication factor infobased on Cassandranone infoSource-replica replication available in experimental statusnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnofine grained access rights according to SQL-standardnono

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More resources
Apache DruidHawkular MetricsMonetDBSpark SQLTerarkDB
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