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DBMS > Drizzle vs. Kinetica vs. Microsoft Azure Table Storage vs. Splice Machine

System Properties Comparison Drizzle vs. Kinetica vs. Microsoft Azure Table Storage vs. Splice Machine

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Table Storage  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.Fully vectorized database across both GPUs and CPUsA Wide Column Store for rapid development using massive semi-structured datasetsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMSWide column storeRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.kinetica.comazure.microsoft.com/­en-us/­services/­storage/­tablessplicemachine.com
Technical documentationdocs.kinetica.comsplicemachine.com/­how-it-works
DeveloperDrizzle project, originally started by Brian AkerKineticaMicrosoftSplice Machine
Initial release2008201220122014
Current release7.2.4, September 20127.1, August 20213.1, March 2021
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialcommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C, C++Java
Server operating systemsFreeBSD
Linux
OS X
LinuxhostedLinux
OS X
Solaris
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesyesnoyes
SQL infoSupport of SQLyes infowith proprietary extensionsSQL-like DML and DDL statementsnoyes
APIs and other access methodsJDBCJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIJDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C++
Java
PHP
C++
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functionsnoyes infoJava
Triggersno infohooks for callbacks inside the server can be used.yes infotriggers when inserted values for one or more columns fall within a specified rangenoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnooptimistic lockingACID
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.yes infoGPU vRAM or System RAMnoyes
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users and roles on table levelAccess rights based on private key authentication or shared access signaturesAccess rights for users, groups and roles according to SQL-standard

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More resources
DrizzleKineticaMicrosoft Azure Table StorageSplice Machine
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