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DBMS > EventStoreDB vs. Google Cloud Spanner vs. GridDB vs. Kdb

System Properties Comparison EventStoreDB vs. Google Cloud Spanner vs. GridDB vs. Kdb

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Editorial information provided by DB-Engines
NameEventStoreDB  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonGridDB  Xexclude from comparisonKdb  Xexclude from comparison
DescriptionIndustrial-strength, open-source database solution built from the ground up for event sourcing.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.Scalable in-memory time series database optimized for IoT and Big DataHigh performance Time Series DBMS
Primary database modelEvent StoreRelational DBMSTime Series DBMSTime Series DBMS
Vector DBMS
Secondary database modelsKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.10
Rank#179  Overall
#1  Event Stores
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Websitewww.eventstore.comcloud.google.com/­spannergriddb.netkx.com
Technical documentationdevelopers.eventstore.comcloud.google.com/­spanner/­docsdocs.griddb.netcode.kx.com
DeveloperEvent Store LimitedGoogleToshiba CorporationKx Systems, a division of First Derivatives plc
Initial release2012201720132000 infokdb was released 2000, kdb+ in 2003
Current release21.2, February 20215.1, August 20223.6, May 2018
License infoCommercial or Open SourceOpen SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial infofree 32-bit version
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++q
Server operating systemsLinux
Windows
hostedLinuxLinux
OS X
Solaris
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyes
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.nonoyes
Secondary indexesyesyesyes infotable attribute 'grouped'
SQL infoSupport of SQLyes infoQuery statements complying to ANSI 2011SQL92, SQL-like TQL (Toshiba Query Language)SQL-like query language (q)
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
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
Server-side scripts infoStored proceduresnonouser defined functions
Triggersnoyesyes infowith views
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication with 3 replicas for regional instances.Source-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud DataflowConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno infosimilar paradigm used for internal processing
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integrityyes 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 dataACID infoStrict serializable isolationACID at container levelno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users can be defined per databaserights management via user accounts
More information provided by the system vendor
EventStoreDBGoogle Cloud SpannerGridDBKdb
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Integrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
provides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
tick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricsGitHub trending repository
» more
kdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
upon request
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
EventStoreDBGoogle Cloud SpannerGridDBKdb
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