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DBMS > Google Cloud Datastore vs. Kinetica vs. TDSQL for MySQL vs. WakandaDB

System Properties Comparison Google Cloud Datastore vs. Kinetica vs. TDSQL for MySQL vs. WakandaDB

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonTDSQL for MySQL  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFully 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.WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelDocument storeRelational DBMSRelational DBMSObject oriented 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
Score4.47
Rank#76  Overall
#12  Document stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.85
Rank#205  Overall
#95  Relational DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websitecloud.google.com/­datastorewww.kinetica.comwww.tencentcloud.com/­products/­dcdbwakanda.github.io
Technical documentationcloud.google.com/­datastore/­docsdocs.kinetica.comwww.tencentcloud.com/­document/­product/­1042wakanda.github.io/­doc
DeveloperGoogleKineticaTencentWakanda SAS
Initial release2008201220132012
Current release7.1, August 20212.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++C++, JavaScript
Server operating systemshostedLinuxhostedLinux
OS X
Windows
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.nononono
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like DML and DDL statementsyesno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
PHP
Python
Ruby
JavaScript
Server-side scripts infoStored proceduresusing Google App Engineuser defined functionsyesyes
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 nodesShardingShardingAutomatic shardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replicationMulti-source replication
Source-replica replication
none
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 pathsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDACID
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 RAMnono
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 conceptyes

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More resources
Google Cloud DatastoreKineticaTDSQL for MySQLWakandaDB
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