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DBMS > Google Cloud Bigtable vs. Kinetica vs. TDSQL for MySQL

System Properties Comparison Google Cloud Bigtable vs. Kinetica vs. TDSQL for MySQL

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonKinetica  Xexclude from comparisonTDSQL for MySQL  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Fully vectorized database across both GPUs and CPUsA high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.
Primary database modelKey-value store
Wide column store
Relational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.85
Rank#205  Overall
#95  Relational DBMS
Websitecloud.google.com/­bigtablewww.kinetica.comwww.tencentcloud.com/­products/­dcdb
Technical documentationcloud.google.com/­bigtable/­docsdocs.kinetica.comwww.tencentcloud.com/­document/­product/­1042
DeveloperGoogleKineticaTencent
Initial release201520122013
Current release7.1, August 2021
License infoCommercial or Open Sourcecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++
Server operating systemshostedLinuxhosted
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.nonono
Secondary indexesnoyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyes
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
PHP
Python
Ruby
Server-side scripts infoStored proceduresnouser defined functionsyes
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingAutomatic sharding
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 methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.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 levelUsers with fine-grained authorization concept

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More resources
Google Cloud BigtableKineticaTDSQL for MySQL
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