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

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

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSadas Engine  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionAutomatically 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 environmentsA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelDocument storeKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
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
#158  Relational DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitecloud.google.com/­datastorewww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlwww.sadasengine.comwww.teradata.com
Technical documentationcloud.google.com/­datastore/­docsdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationdocs.teradata.com
DeveloperGoogleOracle infooriginally developed by Sleepycat, which was acquired by OracleSADAS s.r.l.Teradata
Initial release2008199420061984
Current release18.1.40, May 20208.0Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourcecommercialOpen Source infocommercial license availablecommercial infofree trial version availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, Java, C++ (depending on the Berkeley DB edition)C++
Server operating systemshostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
AIX
Linux
Windows
hosted
Linux
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyes, details herenoyesyes
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 editionnoyes
Secondary indexesyesyesyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLSQL-like query language (GQL)yes infoSQL interfaced based on SQLite is availableyesyes infoSQL 2016 + extensions
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
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
.Net
C
C#
C++
Groovy
Java
PHP
Python
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresusing Google App Enginenonoyes infoUDFs, stored procedures, table functions in parallel
TriggersCallbacks using the Google Apps Engineyes infoonly for the SQL APInoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnonehorizontal partitioningSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replicationnoneMulti-source replication
Source-replica replication
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.Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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'yes
User concepts infoAccess controlAccess 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-standardfine grained access rights according to SQL-standard

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More resources
Google Cloud DatastoreOracle Berkeley DBSadas EngineTeradata
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