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DBMS > EventStoreDB vs. Google Cloud Bigtable vs. Kdb vs. Vitess

System Properties Comparison EventStoreDB vs. Google Cloud Bigtable vs. Kdb vs. Vitess

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Editorial information provided by DB-Engines
NameEventStoreDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonKdb  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionIndustrial-strength, open-source database solution built from the ground up for event sourcing.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.High performance Time Series DBMSScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelEvent StoreKey-value store
Wide column store
Time Series DBMS
Vector DBMS
Relational DBMS
Secondary database modelsRelational DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.07
Rank#181  Overall
#1  Event Stores
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score7.73
Rank#45  Overall
#2  Time Series DBMS
#1  Vector DBMS
Score0.86
Rank#202  Overall
#95  Relational DBMS
Websitewww.eventstore.comcloud.google.com/­bigtablekx.comvitess.io
Technical documentationdevelopers.eventstore.comcloud.google.com/­bigtable/­docscode.kx.comvitess.io/­docs
DeveloperEvent Store LimitedGoogleKx Systems, a division of First Derivatives plcThe Linux Foundation, PlanetScale
Initial release201220152000 infokdb was released 2000, kdb+ in 20032013
Current release21.2, February 20213.6, May 201815.0.2, December 2022
License infoCommercial or Open SourceOpen Sourcecommercialcommercial infofree 32-bit versionOpen Source infoApache Version 2.0, commercial licenses 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 languageqGo
Server operating systemsLinux
Windows
hostedLinux
OS X
Solaris
Windows
Docker
Linux
macOS
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or datenoyesyes
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.noyes
Secondary indexesnoyes infotable attribute 'grouped'yes
SQL infoSupport of SQLnoSQL-like query language (q)yes infowith proprietary extensions
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnouser defined functionsyes infoproprietary syntax
Triggersnoyes infowith viewsyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno infosimilar paradigm used for internal processingno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynoyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engine
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)rights management via user accountsUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
EventStoreDBGoogle Cloud BigtableKdbVitess
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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More resources
EventStoreDBGoogle Cloud BigtableKdbVitess
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