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DBMS > Google Cloud Datastore vs. GridGain vs. Oracle NoSQL vs. Teradata Aster

System Properties Comparison Google Cloud Datastore vs. GridGain vs. Oracle NoSQL vs. Teradata Aster

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonGridGain  Xexclude from comparisonOracle NoSQL  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 PlatformGridGain is an in-memory computing platform, built on Apache IgniteA multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodesPlatform for big data analytics on multistructured data sources and types
Primary database modelDocument storeKey-value store
Relational DBMS
Document store
Key-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score3.05
Rank#97  Overall
#17  Document stores
#16  Key-value stores
#50  Relational DBMS
Websitecloud.google.com/­datastorewww.gridgain.comwww.oracle.com/­database/­nosql/­technologies/­nosql
Technical documentationcloud.google.com/­datastore/­docswww.gridgain.com/­docs/­index.htmldocs.oracle.com/­en/­database/­other-databases/­nosql-database/­index.html
DeveloperGoogleGridGain Systems, Inc.OracleTeradata
Initial release2008200720112005
Current releaseGridGain 8.5.124.1, May 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoProprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)commercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetJava
Server operating systemshostedLinux
OS X
Solaris
Windows
Linux
Solaris SPARC/x86
Linux
Data schemeschema-freeyesSupport Fixed schema and Schema-less deployment with the ability to interoperate between them.Flexible 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 hereyesoptionalyes
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.noyesnoyes infoin Aster File Store
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query language (GQL)ANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statementsyes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
RESTful HTTP APIADO.NET
JDBC
ODBC
OLE DB
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
C
C#
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresusing Google App Engineyes (compute grid and cache interceptors can be used instead)noR packages
TriggersCallbacks using the Google Apps Engineyes (cache interceptors and events)nono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes (replicated cache)Electable source-replica replication per shard. Support distributed global deployment with Multi-region table featureyes 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 Dataflowyes (compute grid and hadoop accelerator)with Hadoop integrationyes 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 ConsistencyEventual Consistency
Immediate Consistency infodepending on configuration
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDconfigurable infoACID within a storage node (=shard)ACID
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.noyesyes infooff heap cacheno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementationsAccess rights for users and rolesfine grained access rights according to SQL-standard

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More resources
Google Cloud DatastoreGridGainOracle NoSQLTeradata Aster
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