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DBMS > Apache IoTDB vs. Fauna vs. Google Cloud Datastore vs. Lovefield vs. Microsoft Azure AI Search

System Properties Comparison Apache IoTDB vs. Fauna vs. Google Cloud Datastore vs. Lovefield vs. Microsoft Azure AI Search

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonLovefield  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkFauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformEmbeddable relational database for web apps written in pure JavaScriptSearch-as-a-service for web and mobile app development
Primary database modelTime Series DBMSDocument store
Graph DBMS
Relational DBMS
Time Series DBMS
Document storeRelational DBMSSearch engine
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.19
Rank#176  Overall
#15  Time Series DBMS
Score1.55
Rank#154  Overall
#26  Document stores
#14  Graph DBMS
#72  Relational DBMS
#13  Time Series DBMS
Score4.49
Rank#79  Overall
#12  Document stores
Score0.32
Rank#290  Overall
#132  Relational DBMS
Score5.71
Rank#64  Overall
#8  Search engines
Websiteiotdb.apache.orgfauna.comcloud.google.com/­datastoregoogle.github.io/­lovefieldazure.microsoft.com/­en-us/­services/­search
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.fauna.comcloud.google.com/­datastore/­docsgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdlearn.microsoft.com/­en-us/­azure/­search
DeveloperApache Software FoundationFauna, Inc.GoogleGoogleMicrosoft
Initial release20182014200820142015
Current release1.1.0, April 20232.1.12, February 2017V1
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyesyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScalaJavaScript
Server operating systemsAll OS with a Java VM (>= 1.8)hostedhostedserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, Safarihosted
Data schemeyesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyes, details hereyesyes
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 indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like query languagenoSQL-like query language (GQL)SQL-like query language infovia JavaScript builder patternno
APIs and other access methodsJDBC
Native API
RESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaScriptC#
Java
JavaScript
Python
Server-side scripts infoStored proceduresyesuser defined functionsusing Google App Enginenono
TriggersyesnoCallbacks using the Google Apps EngineUsing read-only observersno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioning infoconsistent hashingShardingnoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replicationMulti-source replication using Paxosnoneyes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate 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 integritynoyesyes infovia ReferenceProperties or Ancestor pathsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes infousing MemoryDBno
User concepts infoAccess controlyesIdentity management, authentication, and access controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noyes infousing Azure authentication

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More resources
Apache IoTDBFauna infopreviously named FaunaDBGoogle Cloud DatastoreLovefieldMicrosoft Azure AI Search
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