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DBMS > Apache IoTDB vs. Lovefield vs. Microsoft Azure Data Explorer vs. Microsoft Azure Synapse Analytics vs. Stardog

System Properties Comparison Apache IoTDB vs. Lovefield vs. Microsoft Azure Data Explorer vs. Microsoft Azure Synapse Analytics vs. Stardog

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonLovefield  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonStardog  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 FlinkEmbeddable relational database for web apps written in pure JavaScriptFully managed big data interactive analytics platformElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelTime Series DBMSRelational DBMSRelational DBMS infocolumn orientedRelational DBMSGraph DBMS
RDF store
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
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.29
Rank#293  Overall
#133  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websiteiotdb.apache.orggoogle.github.io/­lovefieldazure.microsoft.com/­services/­data-explorerazure.microsoft.com/­services/­synapse-analyticswww.stardog.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mddocs.microsoft.com/­en-us/­azure/­data-explorerdocs.microsoft.com/­azure/­synapse-analyticsdocs.stardog.com
DeveloperApache Software FoundationGoogleMicrosoftMicrosoftStardog-Union
Initial release20182014201920162010
Current release1.1.0, April 20232.1.12, February 2017cloud service with continuous releases7.3.0, May 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0commercialcommercialcommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaScriptC++Java
Server operating systemsAll OS with a Java VM (>= 1.8)server-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafarihostedhostedLinux
macOS
Windows
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)yesschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes
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.nonoyesnono infoImport/export of XML data possible
Secondary indexesyesyesall fields are automatically indexedyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLSQL-like query languageSQL-like query language infovia JavaScript builder patternKusto Query Language (KQL), SQL subsetyesYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsJDBC
Native API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
ODBC
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
JavaScript.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C#
Java
PHP
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresyesnoYes, possible languages: KQL, Python, RTransact SQLuser defined functions and aggregates, HTTP Server extensions in Java
TriggersyesUsing read-only observersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneSharding infoImplicit feature of the cloud serviceSharding, horizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnoneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yesMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparknoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integritynoyesnono 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 datanoACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infousing MemoryDBnoyes
User concepts infoAccess controlyesnoAzure Active Directory AuthenticationyesAccess rights for users and roles

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More resources
Apache IoTDBLovefieldMicrosoft Azure Data ExplorerMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseStardog
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