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DBMS > Google Cloud Datastore vs. Oracle Berkeley DB vs. OrigoDB vs. Rockset

System Properties Comparison Google Cloud Datastore vs. Oracle Berkeley DB vs. OrigoDB vs. Rockset

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonOrigoDB  Xexclude from comparisonRockset  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformWidely used in-process key-value storeA fully ACID in-memory object graph databaseA scalable, reliable search and analytics service in the cloud, built on RocksDB
Primary database modelDocument storeKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Document store
Object oriented DBMS
Document store
Secondary database modelsRelational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Score0.79
Rank#211  Overall
#35  Document stores
Websitecloud.google.com/­datastorewww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlorigodb.comrockset.com
Technical documentationcloud.google.com/­datastore/­docsdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlorigodb.com/­docsdocs.rockset.com
DeveloperGoogleOracle infooriginally developed by Sleepycat, which was acquired by OracleRobert Friberg et alRockset
Initial release200819942009 infounder the name LiveDB2019
Current release18.1.40, May 2020
License infoCommercial or Open SourcecommercialOpen Source infocommercial license availableOpen Sourcecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, Java, C++ (depending on the Berkeley DB edition)C#C++
Server operating systemshostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
Windows
hosted
Data schemeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyes, details herenoUser defined using .NET types and collectionsdynamic typing
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.noyes infoonly with the Berkeley DB XML editionno infocan be achieved using .NETno infoingestion from XML files supported
Secondary indexesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLSQL-like query language (GQL)yes infoSQL interfaced based on SQLite is availablenoRead-only SQL queries, including JOINs
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
HTTP API
LINQ
HTTP REST
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
.NetGo
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresusing Google App Enginenoyesno
TriggersCallbacks using the Google Apps Engineyes infoonly for the SQL APIyes infoDomain Eventsno
Partitioning methods infoMethods for storing different data on different nodesShardingnonehorizontal partitioning infoclient side managed; servers are not synchronizedAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replicationSource-replica replicationyes
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.Eventual Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnodepending on modelno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infoWrite ahead logyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noRole based authorizationAccess rights for users and organizations can be defined via Rockset console

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More resources
Google Cloud DatastoreOracle Berkeley DBOrigoDBRockset
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