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DBMS > HugeGraph vs. Kinetica vs. Microsoft Azure Data Explorer vs. TimesTen

System Properties Comparison HugeGraph vs. Kinetica vs. Microsoft Azure Data Explorer vs. TimesTen

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Editorial information provided by DB-Engines
NameHugeGraph  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionA fast-speed and highly-scalable Graph DBMSFully vectorized database across both GPUs and CPUsFully managed big data interactive analytics platformIn-Memory RDBMS compatible to Oracle
Primary database modelGraph DBMSRelational DBMSRelational DBMS infocolumn orientedRelational DBMS
Secondary database modelsSpatial DBMS
Time Series 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
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score1.31
Rank#163  Overall
#74  Relational DBMS
Websitegithub.com/­hugegraph
hugegraph.apache.org
www.kinetica.comazure.microsoft.com/­services/­data-explorerwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationhugegraph.apache.org/­docsdocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­database/­timesten-18.1
DeveloperBaiduKineticaMicrosoftOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release2018201220191998
Current release0.97.1, August 2021cloud service with continuous releases11 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++
Server operating systemsLinux
macOS
Unix
LinuxhostedAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyesyesFixed 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.nonoyesno
Secondary indexesyes infoalso supports composite index and range indexyesall fields are automatically indexedyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetyes
APIs and other access methodsJava API
RESTful HTTP API
TinkerPop Gremlin
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesGroovy
Java
Python
C++
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresasynchronous Gremlin script jobsuser defined functionsYes, possible languages: KQL, Python, RPL/SQL
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseShardingSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsvia hugegraph-sparknoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infoedges in graphyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAMnoyes
User concepts infoAccess controlUsers, roles and permissionsAccess rights for users and roles on table levelAzure Active Directory Authenticationfine grained access rights according to SQL-standard

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More resources
HugeGraphKineticaMicrosoft Azure Data ExplorerTimesTen
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