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DBMS > chDB vs. Google Cloud Datastore vs. Kinetica vs. Microsoft Azure SQL Database vs. Postgres-XL

System Properties Comparison chDB vs. Google Cloud Datastore vs. Kinetica vs. Microsoft Azure SQL Database vs. Postgres-XL

Editorial information provided by DB-Engines
NamechDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonPostgres-XL  Xexclude from comparison
DescriptionAn embedded SQL OLAP Engine powered by ClickHouseAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFully vectorized database across both GPUs and CPUsDatabase as a Service offering with high compatibility to Microsoft SQL ServerBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelRelational DBMSDocument storeRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsTime Series DBMSSpatial DBMS
Time Series DBMS
Document store
Graph DBMS
Spatial DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.07
Rank#376  Overall
#158  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score76.78
Rank#16  Overall
#11  Relational DBMS
Score0.53
Rank#254  Overall
#117  Relational DBMS
Websitegithub.com/­chdb-io/­chdbcloud.google.com/­datastorewww.kinetica.comazure.microsoft.com/­en-us/­products/­azure-sql/­databasewww.postgres-xl.org
Technical documentationdoc.chdb.iocloud.google.com/­datastore/­docsdocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­azure-sqlwww.postgres-xl.org/­documentation
DeveloperGoogleKineticaMicrosoft
Initial release20232008201220102014 infosince 2012, originally named StormDB
Current release7.1, August 2021V1210 R1, October 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercialOpen Source infoMozilla public license
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++C++C
Server operating systemsserver-lesshostedLinuxhostedLinux
macOS
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyes, details hereyesyesyes
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.nonoyesyes infoXML type, but no XML query functionality
Secondary indexesyesyesyesyes
SQL infoSupport of SQLClose to ANSI SQL (SQL/JSON + extensions)SQL-like query language (GQL)SQL-like DML and DDL statementsyesyes infodistributed, parallel query execution
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesBun
C
C++
Go
JavaScript (Node.js)
Python
Rust
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresusing Google App Engineuser defined functionsTransact SQLuser defined functions
TriggersCallbacks using the Google Apps Engineyes infotriggers when inserted values for one or more columns fall within a specified rangeyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replicationyes, with always 3 replicas available
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonono
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 Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDACID infoMVCC
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.noyes infoGPU vRAM or System RAMno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table levelfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
chDBGoogle Cloud DatastoreKineticaMicrosoft Azure SQL Database infoformerly SQL AzurePostgres-XL
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