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DBMS > HEAVY.AI vs. InfluxDB vs. Memgraph vs. Microsoft Azure Data Explorer vs. Yanza

Vergleich der Systemeigenschaften HEAVY.AI vs. InfluxDB vs. Memgraph vs. Microsoft Azure Data Explorer vs. Yanza

Redaktionelle Informationen bereitgestellt von DB-Engines
NameHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xaus Vergleich ausschliessenInfluxDB  Xaus Vergleich ausschliessenMemgraph  Xaus Vergleich ausschliessenMicrosoft Azure Data Explorer  Xaus Vergleich ausschliessenYanza  Xaus Vergleich ausschliessen
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
KurzbeschreibungA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareDBMS for storing time series, events and metricsAn open source graph database built for real-time streaming and compatible with Neo4jFully managed big data interactive analytics platformTime Series DBMS for IoT Applications
Primäres DatenbankmodellRelational DBMSTime Series DBMSGraph DBMSRelational DBMS infocolumn orientedTime Series DBMS
Sekundäre DatenbankmodelleSpatial DBMSSpatial DBMS infowith GEO packageDocument 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
Suchmaschine 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 infomisst die Popularität von Datenbankmanagement- systemenranking trend
Trend Chart
Punkte1,77
Rang#141  Overall
#65  Relational DBMS
Punkte25,83
Rang#28  Overall
#1  Time Series DBMS
Punkte3,02
Rang#98  Overall
#8  Graph DBMS
Punkte4,38
Rang#77  Overall
#41  Relational DBMS
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
www.influxdata.com/­products/­influxdb-overviewmemgraph.comazure.microsoft.com/­services/­data-exploreryanza.com
Technische Dokumentationdocs.heavy.aidocs.influxdata.com/­influxdbmemgraph.com/­docsdocs.microsoft.com/­en-us/­azure/­data-explorer
Social network pagesLinkedInTwitterFacebookGitHubDiscord
EntwicklerHEAVY.AI, Inc.Memgraph LtdMicrosoftYanza
Erscheinungsjahr20162013201720192015
Aktuelle Version5.10, Jänner 20222.7.6, April 2024cloud service with continuous releases
Lizenz infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availableOpen Source infoMIT-License; commercial enterprise version availableOpen Source infoBSL 1.1; commercial license for enterprise edition availablekommerziellkommerziell infofree version available
Ausschließlich ein Cloud-Service infoNur als Cloud-Service verfügbarneinneinneinjanein infobut mainly used as a service provided by Yanza
DBaaS Angebote (gesponserte Links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
ImplementierungsspracheC++ and CUDAGoC und C++
Server BetriebssystemeLinuxLinux
OS X infothrough Homebrew
LinuxgehostetWindows
Datenschemajaschemafreischemafrei und schema-optionalFixed schema with schema-less datatypes (dynamic)schemafrei
Typisierung infovordefinierte Datentypen, z.B. float oder datejaNumeric data and Stringsjaja infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesnein
XML Unterstützung infoVerarbeitung von Daten in XML Format, beispielsweise Speicherung von XML-Strukturen und/oder Unterstützung von XPath, XQuery, XSLTneinneinneinjanein
Sekundärindizesneinneinall fields are automatically indexednein
SQL infoSupport of SQLjaSQL-like query languageneinKusto Query Language (KQL), SQL subsetnein
APIs und andere ZugriffskonzepteJDBC
ODBC
Thrift
Vega
HTTP API
JSON over UDP
Bolt protocol
Cypher query language
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP API
Unterstützte ProgrammiersprachenAll languages supporting JDBC/ODBC/Thrift
Python
.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
C
C++
Elixir
Go
Haskell
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
jede Sprache, die HTTP-Aufrufe erlaubt
Server-seitige Scripts infoStored ProceduresneinneinYes, possible languages: KQL, Python, Rnein
Triggersneinneinja infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyja infoTimer and event based
Partitionierungsmechanismen infoMethoden zum Speichern von unterschiedlichen Daten auf unterschiedlichen KnotenSharding infoRound robinSharding infoin enterprise version onlySharding infodynamic graph partitioningSharding infoImplicit feature of the cloud servicekeine
Replikationsmechanismen infoMethoden zum redundanten Speichern von Daten auf mehreren KnotenMulti-Source Replikationfrei wählbarer Replikationsfaktor infoin enterprise version onlyMulti-source replication using RAFTja infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.keine
MapReduce infoBietet ein API für Map/Reduce OperationenneinneinneinSpark connector (open source): github.com/­Azure/­azure-kusto-sparknein
Konsistenzkonzept infoMethoden zur Sicherstellung der Konsistenz in einem verteilten SystemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Fremdschlüssel inforeferenzielle Integritätneinneinja inforelationships in graphsneinnein
Transaktionskonzept infoUnterstützung zur Sicherstellung der Datenintegrität bei nicht-atomaren DatenmanipulationenneinneinACID infowith snapshot isolationneinnein
Concurrency infoUnterstützung von gleichzeitig ausgeführten Datenmanipulationenjajayes, multi-version concurrency control (MVCC)jaja
Durability infoDauerhafte Speicherung der Datenjajaja infowith periodic snapshot and write-ahead logging (WAL) of changesjaja
In-Memory Unterstützung infoGibt es Möglichkeiten einige oder alle Strukturen nur im Hauptspeicher zu haltenjaja infoDepending on used storage enginejanein
Berechtigungskonzept infoZugriffskontrolleBenutzer mit feingranularem Berechtigungskonzept entsprechend SQL-StandardEinfache Rechteverwaltung mit BenutzeraccountsUsers, roles and permissionsAzure Active Directory Authenticationnein
Weitere Informationen bereitgestellt vom Systemhersteller
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022InfluxDBMemgraphMicrosoft Azure Data ExplorerYanza
Specific characteristicsInfluxData is the creator of InfluxDB , the open source time series database. It...
» mehr
Memgraph directly connects to your streaming infrastructure so you and your team...
» mehr
Competitive advantagesTime to Value InfluxDB is available in all the popular languages and frameworks,...
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Business Source License ensures a future for the Memgraph community MAGE algorithm...
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Typical application scenariosIoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
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Graph algorithms in bioinformatics Social network analysis Cryptocurrency network...
» mehr
Key customersInfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
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Market metricsFastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» mehr
Licensing and pricing modelsOpen source core with closed source clustering available either on-premise or on...
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You can check out our pricing model and licenses on the company website .
» mehr
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Weitere Ressourcen
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022InfluxDBMemgraphMicrosoft Azure Data ExplorerYanza
DB-Engines Blog Posts

Why Build a Time Series Data Platform?
20. Juli 2017, Paul Dix (guest author)

Time Series DBMS are the database category with the fastest increase in popularity
4. Juli 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1. Juni 2015, Paul Andlinger

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