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DBMS > Google Cloud Datastore vs. Graph Engine vs. Lovefield vs. Microsoft Azure Synapse Analytics vs. TinkerGraph

System Properties Comparison Google Cloud Datastore vs. Graph Engine vs. Lovefield vs. Microsoft Azure Synapse Analytics vs. TinkerGraph

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonLovefield  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonTinkerGraph  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineEmbeddable relational database for web apps written in pure JavaScriptElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API
Primary database modelDocument storeGraph DBMS
Key-value store
Relational DBMSRelational DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score0.29
Rank#293  Overall
#133  Relational DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score0.08
Rank#348  Overall
#35  Graph DBMS
Websitecloud.google.com/­datastorewww.graphengine.iogoogle.github.io/­lovefieldazure.microsoft.com/­services/­synapse-analyticstinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlin
Technical documentationcloud.google.com/­datastore/­docswww.graphengine.io/­docs/­manualgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mddocs.microsoft.com/­azure/­synapse-analytics
DeveloperGoogleMicrosoftGoogleMicrosoft
Initial release20082010201420162009
Current release2.1.12, February 2017
License infoCommercial or Open SourcecommercialOpen Source infoMIT LicenseOpen Source infoApache 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation language.NET and CJavaScriptC++Java
Server operating systemshosted.NETserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, Safarihosted
Data schemeschema-freeyesyesyesschema-free
Typing infopredefined data types such as float or dateyes, details hereyesyesyesyes
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.nonononono
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like query language (GQL)noSQL-like query language infovia JavaScript builder patternyesno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP APIADO.NET
JDBC
ODBC
TinkerPop 3
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
F#
Visual Basic
JavaScriptC#
Java
PHP
Groovy
Java
Server-side scripts infoStored proceduresusing Google App EngineyesnoTransact SQLno
TriggersCallbacks using the Google Apps EnginenoUsing read-only observersnono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningnoneSharding, horizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosnoneyesnone
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 Consistencynone
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyesno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesno
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesoptional
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infousing MemoryDByes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noyesno

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More resources
Google Cloud DatastoreGraph Engine infoformer name: TrinityLovefieldMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseTinkerGraph
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