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DBMS > Drizzle vs. Google Cloud Spanner vs. HarperDB vs. Kinetica

System Properties Comparison Drizzle vs. Google Cloud Spanner vs. HarperDB vs. Kinetica

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonHarperDB  Xexclude from comparisonKinetica  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.Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Fully vectorized database across both GPUs and CPUs
Primary database modelRelational DBMSRelational DBMSDocument storeRelational 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
Score0.55
Rank#252  Overall
#38  Document stores
Score0.69
Rank#234  Overall
#107  Relational DBMS
Websitecloud.google.com/­spannerwww.harperdb.iowww.kinetica.com
Technical documentationcloud.google.com/­spanner/­docsdocs.harperdb.io/­docsdocs.kinetica.com
DeveloperDrizzle project, originally started by Brian AkerGoogleHarperDBKinetica
Initial release2008201720172012
Current release7.2.4, September 20123.1, August 20217.1, August 2021
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialcommercial infofree community edition availablecommercial
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++Node.jsC, C++
Server operating systemsFreeBSD
Linux
OS X
hostedLinux
OS X
Linux
Data schemeyesyesdynamic schemayes
Typing infopredefined data types such as float or dateyesyesyes infoJSON data typesyes
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 indexesyesyesyesyes
SQL infoSupport of SQLyes infowith proprietary extensionsyes infoQuery statements complying to ANSI 2011SQL-like data manipulation statementsSQL-like DML and DDL statements
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
React Hooks
RESTful HTTP/JSON API
WebSocket
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC
C++
Java
PHP
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnonoCustom Functions infosince release 3.1user defined functions
Triggersno infohooks for callbacks inside the server can be used.nonoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingShardingA table resides as a whole on one (or more) nodes in a clusterSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication with 3 replicas for regional instances.yes infothe nodes on which a table resides can be definedSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoStrict serializable isolationAtomic execution of specific operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes, using LMDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoGPU vRAM or System RAM
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 rolesAccess rights for users and roles on table level

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More resources
DrizzleGoogle Cloud SpannerHarperDBKinetica
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