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DBMS > Drizzle vs. Hawkular Metrics vs. HBase vs. Splice Machine

System Properties Comparison Drizzle vs. Hawkular Metrics vs. HBase vs. Splice Machine

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHBase  Xexclude from comparisonSplice Machine  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Wide-column store based on Apache Hadoop and on concepts of BigTableOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSTime Series DBMSWide column storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.04
Rank#374  Overall
#38  Time Series DBMS
Score31.25
Rank#26  Overall
#2  Wide column stores
Score0.54
Rank#255  Overall
#116  Relational DBMS
Websitewww.hawkular.orghbase.apache.orgsplicemachine.com
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidehbase.apache.org/­book.htmlsplicemachine.com/­how-it-works
DeveloperDrizzle project, originally started by Brian AkerCommunity supported by Red HatApache Software Foundation infoApache top-level project, originally developed by PowersetSplice Machine
Initial release2008201420082014
Current release7.2.4, September 20122.3.4, January 20213.1, March 2021
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoApache 2.0Open Source infoApache version 2Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaJavaJava
Server operating systemsFreeBSD
Linux
OS X
Linux
OS X
Windows
Linux
Unix
Windows infousing Cygwin
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeschema-free, schema definition possibleyes
Typing infopredefined data types such as float or dateyesyesoptions to bring your own types, AVROyes
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.nono
Secondary indexesyesnonoyes
SQL infoSupport of SQLyes infowith proprietary extensionsnonoyes
APIs and other access methodsJDBCHTTP RESTJava API
RESTful HTTP API
Thrift
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C++
Java
PHP
Go
Java
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonoyes infoCoprocessors in Javayes infoJava
Triggersno infohooks for callbacks inside the server can be used.yes infovia Hawkular Alertingyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication factor infobased on CassandraMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoSingle row ACID (across millions of columns)ACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
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.noyesyes
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPnoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights for users, groups and roles according to SQL-standard

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More resources
DrizzleHawkular MetricsHBaseSplice Machine
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