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DBMS > chDB vs. Google Cloud Datastore vs. IBM Db2 vs. Kinetica vs. Microsoft Azure SQL Database

System Properties Comparison chDB vs. Google Cloud Datastore vs. IBM Db2 vs. Kinetica vs. Microsoft Azure SQL Database

Editorial information provided by DB-Engines
NamechDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIBM Db2 infoformerly named DB2 or IBM Database 2  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparison
DescriptionAn embedded SQL OLAP Engine powered by ClickHouseAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformCommon in IBM host environments, 2 different versions for host and Windows/LinuxFully vectorized database across both GPUs and CPUsDatabase as a Service offering with high compatibility to Microsoft SQL Server
Primary database modelRelational DBMSDocument storeRelational DBMS infoSince Version 10.5 support for JSON/BSON documents compatible with MongoDBRelational DBMSRelational DBMS
Secondary database modelsTime Series DBMSDocument store
RDF store infoin Db2 LUW (Linux, Unix, Windows)
Spatial DBMS infowith Db2 Spatial Extender
Spatial DBMS
Time Series DBMS
Document store
Graph DBMS
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
Score125.90
Rank#9  Overall
#6  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score76.78
Rank#16  Overall
#11  Relational DBMS
Websitegithub.com/­chdb-io/­chdbcloud.google.com/­datastorewww.ibm.com/­products/­db2www.kinetica.comazure.microsoft.com/­en-us/­products/­azure-sql/­database
Technical documentationdoc.chdb.iocloud.google.com/­datastore/­docswww.ibm.com/­docs/­en/­db2docs.kinetica.comdocs.microsoft.com/­en-us/­azure/­azure-sql
DeveloperGoogleIBMKineticaMicrosoft
Initial release202320081983 infohost version20122010
Current release12.1, October 20167.1, August 2021V12
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial infofree version is availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++C, C++C++
Server operating systemsserver-lesshostedAIX
HP-UX
Linux
Solaris
Windows
z/OS
Linuxhosted
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.nonoyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLClose to ANSI SQL (SQL/JSON + extensions)SQL-like query language (GQL)yesSQL-like DML and DDL statementsyes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
JSON style queries infoMongoDB compatible
ODBC
XQuery
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
Supported programming languagesBun
C
C++
Go
JavaScript (Node.js)
Python
Rust
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic
C++
Java
JavaScript (Node.js)
Python
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresusing Google App Engineyesuser defined functionsTransact SQL
TriggersCallbacks using the Google Apps Engineyesyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoonly with Windows/Unix/Linux VersionSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes infowith separate tools (MQ, InfoSphere)Source-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 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 TransactionsACIDnoACID
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 RAM
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-standardAccess rights for users and roles on table levelfine grained access rights according to SQL-standard

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More resources
chDBGoogle Cloud DatastoreIBM Db2 infoformerly named DB2 or IBM Database 2KineticaMicrosoft Azure SQL Database infoformerly SQL Azure
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