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DBMS > Drizzle vs. Google Cloud Spanner vs. Kinetica vs. Splice Machine

System Properties Comparison Drizzle vs. Google Cloud Spanner vs. Kinetica vs. Splice Machine

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonKinetica  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.A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Fully vectorized database across both GPUs and CPUsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.89
Rank#105  Overall
#53  Relational DBMS
Score0.69
Rank#234  Overall
#107  Relational DBMS
Score0.54
Rank#255  Overall
#116  Relational DBMS
Websitecloud.google.com/­spannerwww.kinetica.comsplicemachine.com
Technical documentationcloud.google.com/­spanner/­docsdocs.kinetica.comsplicemachine.com/­how-it-works
DeveloperDrizzle project, originally started by Brian AkerGoogleKineticaSplice Machine
Initial release2008201720122014
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 servicenoyesnono
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
hostedLinuxLinux
OS X
Solaris
Windows
Data schemeyesyesyesyes
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 indexesyesyesyesyes
SQL infoSupport of SQLyes infowith proprietary extensionsyes infoQuery statements complying to ANSI 2011SQL-like DML and DDL statementsyes
APIs and other access methodsJDBCgRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C++
Java
PHP
Go
Java
JavaScript (Node.js)
Python
C++
Java
JavaScript (Node.js)
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonouser defined functionsyes infoJava
Triggersno infohooks for callbacks inside the server can be used.noyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication with 3 replicas for regional instances.Source-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud DataflownoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoStrict serializable isolationnoACID
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.noyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table levelAccess rights for users, groups and roles according to SQL-standard

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More resources
DrizzleGoogle Cloud SpannerKineticaSplice Machine
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