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DBMS > AllegroGraph vs. Kinetica vs. Microsoft Azure Data Explorer vs. Quasardb vs. Riak KV

System Properties Comparison AllegroGraph vs. Kinetica vs. Microsoft Azure Data Explorer vs. Quasardb vs. Riak KV

Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonQuasardb  Xexclude from comparisonRiak KV  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSFully vectorized database across both GPUs and CPUsFully managed big data interactive analytics platformDistributed, high-performance timeseries databaseDistributed, fault tolerant key-value store
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Relational DBMSRelational DBMS infocolumn orientedTime Series DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexes
Secondary database modelsSpatial DBMSSpatial 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
Score1.06
Rank#187  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#7  Vector DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Websiteallegrograph.comwww.kinetica.comazure.microsoft.com/­services/­data-explorerquasar.ai
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmldocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­data-explorerdoc.quasar.ai/­masterwww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperFranz Inc.KineticaMicrosoftquasardbOpenSource, formerly Basho Technologies
Initial release20042012201920092009
Current release8.0, December 20237.1, August 2021cloud service with continuous releases3.14.1, January 20243.2.0, December 2022
License infoCommercial or Open Sourcecommercial infoLimited community edition freecommercialcommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++C++Erlang
Server operating systemsLinux
OS X
Windows
LinuxhostedBSD
Linux
OS X
Windows
Linux
OS X
Data schemeyes infoRDF schemasyesFixed schema with schema-less datatypes (dynamic)schema-freeschema-free
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 infointeger and binaryno
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.no infobulk load of XML files possiblenoyesnono
Secondary indexesyesyesall fields are automatically indexedyes infowith tagsrestricted
SQL infoSupport of SQLSPARQL is used as query languageSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetSQL-like query languageno
APIs and other access methodsRESTful HTTP API
SPARQL
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP APIHTTP API
Native Erlang Interface
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispuser defined functionsYes, possible languages: KQL, Python, RnoErlang
Triggersyesyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodeswith FederationShardingSharding infoImplicit feature of the cloud serviceSharding infoconsistent hashingSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication with selectable replication factorselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkwith Hadoop integrationyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnonono infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAMnoyes infoTransient mode
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationAccess rights for users and roles on table levelAzure Active Directory AuthenticationCryptographically strong user authentication and audit trailyes, using Riak Security
More information provided by the system vendor
AllegroGraphKineticaMicrosoft Azure Data ExplorerQuasardbRiak KV
Specific characteristicsKnowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more
Competitive advantagesAllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more
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