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DBMS > HugeGraph vs. Ignite vs. Microsoft Azure Data Explorer vs. Spark SQL vs. Stardog

System Properties Comparison HugeGraph vs. Ignite vs. Microsoft Azure Data Explorer vs. Spark SQL vs. Stardog

Editorial information provided by DB-Engines
NameHugeGraph  Xexclude from comparisonIgnite  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSpark SQL  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionA fast-speed and highly-scalable Graph DBMSApache 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 platformSpark SQL is a component on top of 'Spark Core' for structured data processingEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelGraph DBMSKey-value store
Relational DBMS
Relational DBMS infocolumn orientedRelational DBMSGraph DBMS
RDF store
Secondary database modelsDocument 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
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websitegithub.com/­hugegraph
hugegraph.apache.org
ignite.apache.orgazure.microsoft.com/­services/­data-explorerspark.apache.org/­sqlwww.stardog.com
Technical documentationhugegraph.apache.org/­docsapacheignite.readme.io/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.stardog.com
DeveloperBaiduApache Software FoundationMicrosoftApache Software FoundationStardog-Union
Initial release20182015201920142010
Current release0.9Apache Ignite 2.6cloud service with continuous releases3.5.0 ( 2.13), September 20237.3.0, May 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0commercialOpen Source infoApache 2.0commercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, Java, .NetScalaJava
Server operating systemsLinux
macOS
Unix
Linux
OS X
Solaris
Windows
hostedLinux
OS X
Windows
Linux
macOS
Windows
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)yesschema-free and OWL/RDFS-schema support
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-typesyesyes
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.noyesyesnono infoImport/export of XML data possible
Secondary indexesyes infoalso supports composite index and range indexyesall fields are automatically indexednoyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLnoANSI-99 for query and DML statements, subset of DDLKusto Query Language (KQL), SQL subsetSQL-like DML and DDL statementsYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsJava API
RESTful HTTP API
TinkerPop Gremlin
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languagesGroovy
Java
Python
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
Python
R
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresasynchronous Gremlin script jobsyes (compute grid and cache interceptors can be used instead)Yes, possible languages: KQL, Python, Rnouser defined functions and aggregates, HTTP Server extensions in Java
Triggersnoyes (cache interceptors and events)yes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes infovia event handlers
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 serviceyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseyes (replicated cache)yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsvia hugegraph-sparkyes (compute grid and hadoop accelerator)Spark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency in HA-Cluster
Foreign keys infoReferential integrityyes infoedges in graphnononoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonoACID
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.yesyesnonoyes
User concepts infoAccess controlUsers, roles and permissionsSecurity Hooks for custom implementationsAzure Active Directory AuthenticationnoAccess rights for users and roles

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More resources
HugeGraphIgniteMicrosoft Azure Data ExplorerSpark SQLStardog
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