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DBMS > Google Cloud Datastore vs. Kinetica vs. Manticore Search vs. openGemini

System Properties Comparison Google Cloud Datastore vs. Kinetica vs. Manticore Search vs. openGemini

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonManticore Search  Xexclude from comparisonopenGemini  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFully vectorized database across both GPUs and CPUsMulti-storage database for search, including full-text search.An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability
Primary database modelDocument storeRelational DBMSSearch engineTime Series DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Time Series DBMS infousing the Manticore Columnar Library
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.29
Rank#302  Overall
#21  Search engines
Score0.09
Rank#361  Overall
#37  Time Series DBMS
Websitecloud.google.com/­datastorewww.kinetica.commanticoresearch.comwww.opengemini.org
github.com/­openGemini
Technical documentationcloud.google.com/­datastore/­docsdocs.kinetica.commanual.manticoresearch.comdocs.opengemini.org/­guide
DeveloperGoogleKineticaManticore SoftwareHuawei and openGemini community
Initial release2008201220172022
Current release7.1, August 20216.0, February 20231.1, July 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL version 2Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++C++Go
Server operating systemshostedLinuxFreeBSD
Linux
macOS
Windows
Linux
Windows
Data schemeschema-freeyesFixed schemaschema-free
Typing infopredefined data types such as float or dateyes, details hereyesInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, BooleanInteger, Float, Boolean, String
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.nonoCan index from XMLno
Secondary indexesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like DML and DDL statementsSQL-like query languageSQL-like query language
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
HTTP REST
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
C
C++
Go
Java
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresusing Google App Engineuser defined functionsuser defined functionsno
TriggersCallbacks using the Google Apps Engineyes infotriggers when inserted values for one or more columns fall within a specified rangenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replicationSynchronous replication based on Galera libraryyes
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 configuration
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnoyes infoisolated transactions for atomic changes and binary logging for safe writesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Manticore index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAMyes
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 levelnoAdministrators and common users accounts

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More resources
Google Cloud DatastoreKineticaManticore SearchopenGemini
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