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DBMS > chDB vs. Google Cloud Datastore vs. Hawkular Metrics vs. Kinetica vs. Microsoft Azure SQL Database

System Properties Comparison chDB vs. Google Cloud Datastore vs. Hawkular Metrics vs. Kinetica vs. Microsoft Azure SQL Database

Editorial information provided by DB-Engines
NamechDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHawkular Metrics  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 PlatformHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Fully vectorized database across both GPUs and CPUsDatabase as a Service offering with high compatibility to Microsoft SQL Server
Primary database modelRelational DBMSDocument storeTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsTime Series DBMSSpatial 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
Score0.08
Rank#366  Overall
#39  Time Series 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.hawkular.orgwww.kinetica.comazure.microsoft.com/­en-us/­products/­azure-sql/­database
Technical documentationdoc.chdb.iocloud.google.com/­datastore/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­azure-sql
DeveloperGoogleCommunity supported by Red HatKineticaMicrosoft
Initial release20232008201420122010
Current release7.1, August 2021V12
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0commercialcommercial
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 languageJavaC, C++C++
Server operating systemsserver-lesshostedLinux
OS X
Windows
Linuxhosted
Data schemeschema-freeschema-freeyesyes
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.nononoyes
Secondary indexesyesnoyesyes
SQL infoSupport of SQLClose to ANSI SQL (SQL/JSON + extensions)SQL-like query language (GQL)noSQL-like DML and DDL statementsyes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP RESTJDBC
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
Go
Java
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresusing Google App Enginenouser defined functionsTransact SQL
TriggersCallbacks using the Google Apps Engineyes infovia Hawkular Alertingyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosselectable replication factor infobased on CassandraSource-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.Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnonoACID
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 infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAccess rights for users and roles on table levelfine grained access rights according to SQL-standard

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More resources
chDBGoogle Cloud DatastoreHawkular MetricsKineticaMicrosoft Azure SQL Database infoformerly SQL Azure
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