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DBMS > Google Cloud Datastore vs. Lovefield vs. Microsoft Azure Data Explorer vs. Pinecone

System Properties Comparison Google Cloud Datastore vs. Lovefield vs. Microsoft Azure Data Explorer vs. Pinecone

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonLovefield  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPinecone  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformEmbeddable relational database for web apps written in pure JavaScriptFully managed big data interactive analytics platformA managed, cloud-native vector database
Primary database modelDocument storeRelational DBMSRelational DBMS infocolumn orientedVector DBMS
Secondary database modelsDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score0.29
Rank#293  Overall
#133  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score3.16
Rank#95  Overall
#2  Vector DBMS
Websitecloud.google.com/­datastoregoogle.github.io/­lovefieldazure.microsoft.com/­services/­data-explorerwww.pinecone.io
Technical documentationcloud.google.com/­datastore/­docsgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mddocs.microsoft.com/­en-us/­azure/­data-explorerdocs.pinecone.io/­docs/­overview
DeveloperGoogleGoogleMicrosoftPinecone Systems, Inc
Initial release2008201420192019
Current release2.1.12, February 2017cloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScript
Server operating systemshostedserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, Safarihostedhosted
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyes, details hereyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesString, Number, Boolean
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.nonoyesno
Secondary indexesyesyesall fields are automatically indexed
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like query language infovia JavaScript builder patternKusto Query Language (KQL), SQL subsetno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaScript.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Python
Server-side scripts infoStored proceduresusing Google App EnginenoYes, possible languages: KQL, Python, R
TriggersCallbacks using the Google Apps EngineUsing read-only observersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosnoneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud DataflownoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
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
Immediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infousing MemoryDBnono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAzure Active Directory Authentication

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More resources
Google Cloud DatastoreLovefieldMicrosoft Azure Data ExplorerPinecone
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