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DBMS > AnzoGraph DB vs. Apache IoTDB vs. Graph Engine vs. Microsoft Azure Data Explorer vs. Transwarp ArgoDB

System Properties Comparison AnzoGraph DB vs. Apache IoTDB vs. Graph Engine vs. Microsoft Azure Data Explorer vs. Transwarp ArgoDB

Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonApache IoTDB  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTranswarp ArgoDB  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineFully managed big data interactive analytics platformDistributed Analytical Database to replace Hadoop+MPP hybrid architecture
Primary database modelGraph DBMS
RDF store
Time Series DBMSGraph DBMS
Key-value store
Relational DBMS infocolumn orientedRelational 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
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#307  Overall
#24  Graph DBMS
#13  RDF stores
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.07
Rank#350  Overall
#153  Relational DBMS
Websitecambridgesemantics.com/­anzographiotdb.apache.orgwww.graphengine.ioazure.microsoft.com/­services/­data-explorerwww.transwarp.cn/­en/­product/­argodb
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.graphengine.io/­docs/­manualdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.transwarp.cn/­#/­documents-support/­docs?category=ARGODB
DeveloperCambridge SemanticsApache Software FoundationMicrosoftMicrosoftTranswarp
Initial release2018201820102019
Current release2.3, January 20211.1.0, April 2023cloud service with continuous releases
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoApache Version 2.0Open Source infoMIT Licensecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava.NET and C
Server operating systemsLinuxAll OS with a Java VM (>= 1.8).NEThosted
Data schemeSchema-free and OWL/RDFS-schema supportyesyesFixed schema with schema-less datatypes (dynamic)yes
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-typesyes
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.nononoyes
Secondary indexesnoyesall fields are automatically indexedyes
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.SQL-like query languagenoKusto Query Language (KQL), SQL subsetyes
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
JDBC
Native API
RESTful HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC++
Java
Python
C
C#
C++
Go
Java
Python
Scala
C#
C++
F#
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesyesYes, possible languages: KQL, Python, R
Triggersnoyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioningSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-Clusterselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingIntegration with Hadoop and SparkSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityno infonot needed in graphsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlAccess rights for users and rolesyesAzure Active Directory Authentication

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More resources
AnzoGraph DBApache IoTDBGraph Engine infoformer name: TrinityMicrosoft Azure Data ExplorerTranswarp ArgoDB
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