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DBMS > AllegroGraph vs. EsgynDB vs. Ignite vs. Microsoft Azure Data Explorer vs. Riak KV

System Properties Comparison AllegroGraph vs. EsgynDB vs. Ignite vs. Microsoft Azure Data Explorer vs. Riak KV

Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonIgnite  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRiak KV  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Fully managed big data interactive analytics platformDistributed, fault tolerant key-value store
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Relational DBMSKey-value store
Relational DBMS
Relational DBMS infocolumn orientedKey-value store infowith links between data sets and object tags for the creation of secondary indexes
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
Score1.13
Rank#179  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#8  Vector DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score3.11
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score4.01
Rank#79  Overall
#9  Key-value stores
Websiteallegrograph.comwww.esgyn.cnignite.apache.orgazure.microsoft.com/­services/­data-explorer
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmlapacheignite.readme.io/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerwww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperFranz Inc.EsgynApache Software FoundationMicrosoftOpenSource, formerly Basho Technologies
Initial release20042015201520192009
Current release8.0, December 2023Apache Ignite 2.6cloud service with continuous releases3.2.0, December 2022
License infoCommercial or Open Sourcecommercial infoLimited community edition freecommercialOpen Source infoApache 2.0commercialOpen Source infoApache version 2, commercial enterprise edition
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 languageC++, JavaC++, Java, .NetErlang
Server operating systemsLinux
OS X
Windows
LinuxLinux
OS X
Solaris
Windows
hostedLinux
OS X
Data schemeyes infoRDF schemasyesyesFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyesyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesno
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 possiblenoyesyesno
Secondary indexesyesyesyesall fields are automatically indexedrestricted
SQL infoSupport of SQLSPARQL is used as query languageyesANSI-99 for query and DML statements, subset of DDLKusto Query Language (KQL), SQL subsetno
APIs and other access methodsRESTful HTTP API
SPARQL
ADO.NET
JDBC
ODBC
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP API
Native Erlang Interface
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
All languages supporting JDBC/ODBC/ADO.NetC#
C++
Java
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
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 LispJava Stored Proceduresyes (compute grid and cache interceptors can be used instead)Yes, possible languages: KQL, Python, RErlang
Triggersyesnoyes (cache interceptors and events)yes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodeswith FederationShardingShardingSharding infoImplicit feature of the cloud serviceSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication between multi datacentersyes (replicated cache)yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes (compute grid and hadoop accelerator)Spark connector (open source): github.com/­Azure/­azure-kusto-sparkyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynoyesnonono infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationfine grained access rights according to SQL-standardSecurity Hooks for custom implementationsAzure Active Directory Authenticationyes, using Riak Security
More information provided by the system vendor
AllegroGraphEsgynDBIgniteMicrosoft Azure Data ExplorerRiak 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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