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DBMS > Apache IoTDB vs. Datastax Enterprise vs. Graph Engine vs. Machbase Neo vs. Microsoft Azure Data Explorer

System Properties Comparison Apache IoTDB vs. Datastax Enterprise vs. Graph Engine vs. Machbase Neo vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDatastax Enterprise  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonMachbase Neo infoFormer name was Infiniflux  Xexclude from comparisonMicrosoft Azure Data Explorer  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 FlinkDataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineTimeSeries DBMS for AIoT and BigDataFully managed big data interactive analytics platform
Primary database modelTime Series DBMSWide column storeGraph DBMS
Key-value store
Time Series DBMSRelational DBMS infocolumn oriented
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS
Document 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
Score5.80
Rank#60  Overall
#4  Wide column stores
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score0.12
Rank#339  Overall
#30  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websiteiotdb.apache.orgwww.datastax.com/­products/­datastax-enterprisewww.graphengine.iomachbase.comazure.microsoft.com/­services/­data-explorer
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.datastax.comwww.graphengine.io/­docs/­manualmachbase.com/­dbmsdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software FoundationDataStaxMicrosoftMachbaseMicrosoft
Initial release20182011201020132019
Current release1.1.0, April 20236.8, April 2020V8.0, August 2023cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoMIT Licensecommercial infofree test version availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.
Implementation languageJavaJava.NET and CC
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
.NETLinux
macOS
Windows
hosted
Data schemeyesschema-freeyesyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.nonononoyes
Secondary indexesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statements (CQL); Spark SQLnoSQL-like query languageKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
Native API
Proprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
RESTful HTTP APIgRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
F#
Visual Basic
C
C#
C++
Go
Java
JavaScript
PHP infovia ODBC
Python
R infovia ODBC
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyesnoyesnoYes, possible languages: KQL, Python, R
Triggersyesyesnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infono "single point of failure"horizontal partitioningShardingSharding 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 replicasconfigurable replication factor, datacenter aware, advanced replication for edge computingselectable replication factoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparkyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency
Tunable Consistency infoconsistency level can be individually decided with each write operation
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoAtomicity and isolation are supported for single operationsnonono
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 storagenoyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes infovolatile and lookup tableno
User concepts infoAccess controlyesAccess rights for users can be defined per objectsimple password-based access controlAzure Active Directory Authentication
More information provided by the system vendor
Apache IoTDBDatastax EnterpriseGraph Engine infoformer name: TrinityMachbase Neo infoFormer name was InfinifluxMicrosoft Azure Data Explorer
Specific characteristicsDataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more
Competitive advantagesSupporting the following application requirements: Zero downtime - Built on Apache...
» more
Typical application scenariosApplications that must be massively and linearly scalable with 100% uptime and able...
» more
Key customersCapital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more
Market metricsAmong the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more
Licensing and pricing modelsAnnual subscription
» more

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Apache IoTDBDatastax EnterpriseGraph Engine infoformer name: TrinityMachbase Neo infoFormer name was InfinifluxMicrosoft Azure Data Explorer
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