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DBMS > Google Cloud Datastore vs. GridGain vs. Hypertable vs. Oracle Rdb

System Properties Comparison Google Cloud Datastore vs. GridGain vs. Hypertable vs. Oracle Rdb

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonGridGain  Xexclude from comparisonHypertable  Xexclude from comparisonOracle Rdb  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is 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 IgniteAn open source BigTable implementation based on distributed file systems such as Hadoop
Primary database modelDocument storeKey-value store
Relational DBMS
Wide column storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.49
Rank#79  Overall
#12  Document stores
Score1.53
Rank#155  Overall
#26  Key-value stores
#73  Relational DBMS
Score1.08
Rank#187  Overall
#85  Relational DBMS
Websitecloud.google.com/­datastorewww.gridgain.comwww.oracle.com/­database/­technologies/­related/­rdb.html
Technical documentationcloud.google.com/­datastore/­docswww.gridgain.com/­docs/­index.htmlwww.oracle.com/­database/­technologies/­related/­rdb-doc.html
DeveloperGoogleGridGain Systems, Inc.Hypertable Inc.Oracle, originally developed by Digital Equipment Corporation (DEC)
Initial release2008200720091984
Current releaseGridGain 8.5.10.9.8.11, March 20167.4.1.1, 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGNU version 3. Commercial license availablecommercial
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 languageJava, C++, .NetC++
Server operating systemshostedLinux
OS X
Solaris
Windows
Linux
OS X
Windows infoan inofficial Windows port is available
HP Open VMS
Data schemeschema-freeyesschema-freeFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyes, details hereyesnoyes
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.noyesno
Secondary indexesyesyesrestricted infoonly exact value or prefix value scansyes
SQL infoSupport of SQLSQL-like query language (GQL)ANSI-99 for query and DML statements, subset of DDLnoyes
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
C++ API
Thrift
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresusing Google App Engineyes (compute grid and cache interceptors can be used instead)no
TriggersCallbacks using the Google Apps Engineyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes (replicated cache)selectable replication factor on file system level
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyes (compute grid and hadoop accelerator)yesno
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 ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDnoyes, on a single node
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.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementationsno

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More resources
Google Cloud DatastoreGridGainHypertableOracle Rdb
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