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DBMS > EJDB vs. Google Cloud Datastore vs. Oracle Berkeley DB vs. Sadas Engine

System Properties Comparison EJDB vs. Google Cloud Datastore vs. Oracle Berkeley DB vs. Sadas Engine

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Editorial information provided by DB-Engines
NameEJDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSadas Engine  Xexclude from comparison
DescriptionEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformWidely used in-process key-value storeSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments
Primary database modelDocument storeDocument storeKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.27
Rank#297  Overall
#44  Document stores
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
#158  Relational DBMS
Websitegithub.com/­Softmotions/­ejdbcloud.google.com/­datastorewww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlwww.sadasengine.com
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdcloud.google.com/­datastore/­docsdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperSoftmotionsGoogleOracle infooriginally developed by Sleepycat, which was acquired by OracleSADAS s.r.l.
Initial release2012200819942006
Current release18.1.40, May 20208.0
License infoCommercial or Open SourceOpen Source infoGPLv2commercialOpen Source infocommercial license availablecommercial infofree trial version available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC, Java, C++ (depending on the Berkeley DB edition)C++
Server operating systemsserver-lesshostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
AIX
Linux
Windows
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyes infostring, integer, double, bool, date, object_idyes, details herenoyes
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
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)yes infoSQL interfaced based on SQLite is availableyes
APIs and other access methodsin-process shared librarygRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
Supported programming languagesActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
.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
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-side scripts infoStored proceduresnousing Google App Enginenono
TriggersnoCallbacks using the Google Apps Engineyes infoonly for the SQL APIno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication using PaxosSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
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
Foreign keys infoReferential integrityno infotypically not needed, however similar functionality with collection joins possibleyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/Write Lockingyesyes
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 infomanaged by 'Learn by Usage'
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAccess rights for users, groups and roles according to SQL-standard

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More resources
EJDBGoogle Cloud DatastoreOracle Berkeley DBSadas Engine
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