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DBMS > Graph Engine vs. Graphite vs. HEAVY.AI vs. Microsoft Azure Data Explorer vs. VictoriaMetrics

System Properties Comparison Graph Engine vs. Graphite vs. HEAVY.AI vs. Microsoft Azure Data Explorer vs. VictoriaMetrics

Editorial information provided by DB-Engines
NameGraph Engine infoformer name: Trinity  Xexclude from comparisonGraphite  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
DescriptionA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineData logging and graphing tool for time series data infoThe storage layer (fixed size database) is called WhisperA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareFully managed big data interactive analytics platformA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelGraph DBMS
Key-value store
Time Series DBMSRelational DBMSRelational DBMS infocolumn orientedTime Series DBMS
Secondary database modelsSpatial DBMSDocument 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
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score4.57
Rank#73  Overall
#5  Time Series DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score1.32
Rank#162  Overall
#14  Time Series DBMS
Websitewww.graphengine.iogithub.com/­graphite-project/­graphite-webgithub.com/­heavyai/­heavydb
www.heavy.ai
azure.microsoft.com/­services/­data-explorervictoriametrics.com
Technical documentationwww.graphengine.io/­docs/­manualgraphite.readthedocs.iodocs.heavy.aidocs.microsoft.com/­en-us/­azure/­data-explorerdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperMicrosoftChris DavisHEAVY.AI, Inc.MicrosoftVictoriaMetrics
Initial release20102006201620192018
Current release5.10, January 2022cloud service with continuous releasesv1.91, May 2023
License infoCommercial or Open SourceOpen Source infoMIT LicenseOpen Source infoApache 2.0Open Source infoApache Version 2; enterprise edition availablecommercialOpen Source infoApache Version 2.0
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 language.NET and CPythonC++ and CUDAGo
Server operating systems.NETLinux
Unix
LinuxhostedFreeBSD
Linux
macOS
OpenBSD
Data schemeyesyesyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesNumeric data onlyyesyes 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.nononoyesno
Secondary indexesnonoall fields are automatically indexed
SQL infoSupport of SQLnonoyesKusto Query Language (KQL), SQL subsetno
APIs and other access methodsRESTful HTTP APIHTTP API
Sockets
JDBC
ODBC
Thrift
Vega
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesC#
C++
F#
Visual Basic
JavaScript (Node.js)
Python
All languages supporting JDBC/ODBC/Thrift
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyesnonoYes, possible languages: KQL, Python, Rno
Triggersnononoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningnoneSharding infoRound robinSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Synchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonononono
Concurrency infoSupport for concurrent manipulation of datayesyes infolockingyesyesyes
Durability infoSupport for making data persistentoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnono
User concepts infoAccess controlnofine grained access rights according to SQL-standardAzure Active Directory Authentication

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More resources
Graph Engine infoformer name: TrinityGraphiteHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Microsoft Azure Data ExplorerVictoriaMetrics
DB-Engines blog posts

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

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

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