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DBMS > Google Cloud Datastore vs. Oracle Berkeley DB vs. TDSQL for MySQL vs. TigerGraph

System Properties Comparison Google Cloud Datastore vs. Oracle Berkeley DB vs. TDSQL for MySQL vs. TigerGraph

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonTDSQL for MySQL  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformWidely used in-process key-value storeA high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelDocument storeKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSGraph DBMS
Secondary database modelsDocument store
Spatial 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
Score0.85
Rank#205  Overall
#95  Relational DBMS
Score1.83
Rank#139  Overall
#13  Graph DBMS
Websitecloud.google.com/­datastorewww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlwww.tencentcloud.com/­products/­dcdbwww.tigergraph.com
Technical documentationcloud.google.com/­datastore/­docsdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlwww.tencentcloud.com/­document/­product/­1042docs.tigergraph.com
DeveloperGoogleOracle infooriginally developed by Sleepycat, which was acquired by OracleTencent
Initial release2008199420132017
Current release18.1.40, May 2020
License infoCommercial or Open SourcecommercialOpen Source infocommercial license availablecommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
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++
Server operating systemshostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
hostedLinux
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 editionnono
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like query language (GQL)yes infoSQL interfaced based on SQLite is availableyesSQL-like query language (GSQL)
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
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
C
C#
C++
Java
PHP
Python
Ruby
C++
Java
Server-side scripts infoStored proceduresusing Google App Enginenoyesyes
TriggersCallbacks using the Google Apps Engineyes infoonly for the SQL APIyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonoyes
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 integrityyes infovia ReferenceProperties or Ancestor pathsnonoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACIDACID
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.noyesnono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noUsers with fine-grained authorization conceptRole-based access control

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More resources
Google Cloud DatastoreOracle Berkeley DBTDSQL for MySQLTigerGraph
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