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DBMS > Google Cloud Spanner vs. IRONdb vs. KeyDB vs. Kinetica

System Properties Comparison Google Cloud Spanner vs. IRONdb vs. KeyDB vs. Kinetica

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Editorial information provided by DB-Engines
NameGoogle Cloud Spanner  Xexclude from comparisonIRONdb  Xexclude from comparisonKeyDB  Xexclude from comparisonKinetica  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA 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.A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsFully vectorized database across both GPUs and CPUs
Primary database modelRelational DBMSTime Series DBMSKey-value storeRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score0.70
Rank#229  Overall
#32  Key-value stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Websitecloud.google.com/­spannerwww.circonus.com/solutions/time-series-database/github.com/­Snapchat/­KeyDB
keydb.dev
www.kinetica.com
Technical documentationcloud.google.com/­spanner/­docsdocs.circonus.com/irondb/category/getting-starteddocs.keydb.devdocs.kinetica.com
DeveloperGoogleCirconus LLC.EQ Alpha Technology Ltd.Kinetica
Initial release2017201720192012
Current releaseV0.10.20, January 20187.1, August 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoBSD-3commercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++C++C, C++
Server operating systemshostedLinuxLinuxLinux
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramspartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesyes
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 indexesyesnoyes infoby using the Redis Search moduleyes
SQL infoSupport of SQLyes infoQuery statements complying to ANSI 2011SQL-like query language (Circonus Analytics Query Language: CAQL)noSQL-like DML and DDL statements
APIs and other access methodsgRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
HTTP APIProprietary protocol infoRESP - REdis Serialization ProtocoJDBC
ODBC
RESTful HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoyes, in LuaLuauser defined functions
Triggersnononoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodeShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication with 3 replicas for regional instances.configurable replication factor, datacenter awareMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency per node, eventual consistency across nodesEventual Consistency
Strong eventual consistency with CRDTs
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoStrict serializable isolationnoOptimistic locking, atomic execution of commands blocks and scriptsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nosimple password-based access control and ACLAccess rights for users and roles on table level

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More resources
Google Cloud SpannerIRONdbKeyDBKinetica
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