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DBMS > Google Cloud Datastore vs. Kingbase vs. Sequoiadb vs. Solr

System Properties Comparison Google Cloud Datastore vs. Kingbase vs. Sequoiadb vs. Solr

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonKingbase  Xexclude from comparisonSequoiadb  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformAn enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.NewSQL database with distributed OLTP and SQLA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelDocument storeRelational DBMSDocument store
Relational DBMS
Search engine
Secondary database modelsDocument store
Spatial DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score0.50
Rank#257  Overall
#119  Relational DBMS
Score0.50
Rank#258  Overall
#41  Document stores
#120  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websitecloud.google.com/­datastorewww.kingbase.com.cnwww.sequoiadb.comsolr.apache.org
Technical documentationcloud.google.com/­datastore/­docswww.sequoiadb.com/­en/­index.php?m=Files&a=indexsolr.apache.org/­resources.html
DeveloperGoogleBeiJing KINGBASE Information technologies inc.Sequoiadb Ltd.Apache Software Foundation
Initial release2008199920132006
Current releaseV8.0, August 20219.6.1, May 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoServer: AGPL; Client: Apache V2Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and JavaC++Java
Server operating systemshostedLinux
Windows
LinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyes, details hereyesyes infooid, date, timestamp, binary, regexyes infosupports customizable data types and automatic typing
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.noyesnoyes
Secondary indexesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like query language (GQL)Standard with numerous extensionsSQL-like query languageSolr Parallel SQL Interface
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT
proprietary protocol using JSONJava API
RESTful HTTP/JSON API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
.Net
C++
Java
PHP
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresusing Google App Engineuser defined functionsJavaScriptJava plugins
TriggersCallbacks using the Google Apps Engineyesnoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by range, list and hash) and vertical partitioningShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosyesSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDDocument is locked during a transactionoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardsimple password-based access controlyes

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More resources
Google Cloud DatastoreKingbaseSequoiadbSolr
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