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DBMS > Google Cloud Datastore vs. Kinetica vs. Newts vs. searchxml vs. Teradata Aster

System Properties Comparison Google Cloud Datastore vs. Kinetica vs. Newts vs. searchxml vs. Teradata Aster

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonNewts  Xexclude from comparisonsearchxml  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFully vectorized database across both GPUs and CPUsTime Series DBMS based on CassandraDBMS for structured and unstructured content wrapped with an application serverPlatform for big data analytics on multistructured data sources and types
Primary database modelDocument storeRelational DBMSTime Series DBMSNative XML DBMS
Search engine
Relational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
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
Score0.07
Rank#375  Overall
#41  Time Series DBMS
Score0.03
Rank#390  Overall
#7  Native XML DBMS
#24  Search engines
Websitecloud.google.com/­datastorewww.kinetica.comopennms.github.io/­newtswww.searchxml.net/­category/­products
Technical documentationcloud.google.com/­datastore/­docsdocs.kinetica.comgithub.com/­OpenNMS/­newts/­wikiwww.searchxml.net/­support/­handouts
DeveloperGoogleKineticaOpenNMS Groupinformationpartners gmbhTeradata
Initial release20082012201420152005
Current release7.1, August 20211.0
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++JavaC++
Server operating systemshostedLinuxLinux
OS X
Windows
WindowsLinux
Data schemeschema-freeyesschema-freeschema-freeFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyes, details hereyesyesyesyes
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.nononoyesyes infoin Aster File Store
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like DML and DDL statementsnonoyes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
HTTP REST
Java API
RESTful HTTP API
WebDAV
XQuery
XSLT
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
JavaC++ infomost other programming languages supported via APIsC
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresusing Google App Engineuser defined functionsnoyes infoon the application serverR packages
TriggersCallbacks using the Google Apps Engineyes infotriggers when inserted values for one or more columns fall within a specified rangenonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infobased on CassandranoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replicationselectable replication factor infobased on Cassandrayes infosychronisation to multiple collectionsyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownononoyes infoSQL Map-Reduce Framework
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 configurationEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnonomultiple readers, single writerACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAMnonono
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 levelnoDomain, group and role-based access control at the document level and for application servicesfine grained access rights according to SQL-standard

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More resources
Google Cloud DatastoreKineticaNewtssearchxmlTeradata Aster
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