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DBMS > GridGain vs. HugeGraph vs. MarkLogic vs. Microsoft Azure Data Explorer vs. Sadas Engine

System Properties Comparison GridGain vs. HugeGraph vs. MarkLogic vs. Microsoft Azure Data Explorer vs. Sadas Engine

Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonHugeGraph  Xexclude from comparisonMarkLogic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSadas Engine  Xexclude from comparison
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteA fast-speed and highly-scalable Graph DBMSOperational and transactional Enterprise NoSQL databaseFully managed big data interactive analytics platformSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments
Primary database modelKey-value store
Relational DBMS
Graph DBMSDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMS infocolumn orientedRelational DBMS
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
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.07
Rank#373  Overall
#157  Relational DBMS
Websitewww.gridgain.comgithub.com/­hugegraph
hugegraph.apache.org
www.marklogic.comazure.microsoft.com/­services/­data-explorerwww.sadasengine.com
Technical documentationwww.gridgain.com/­docs/­index.htmlhugegraph.apache.org/­docsdocs.marklogic.comdocs.microsoft.com/­en-us/­azure/­data-explorerwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperGridGain Systems, Inc.BaiduMarkLogic Corp.MicrosoftSADAS s.r.l.
Initial release20072018200120192006
Current releaseGridGain 8.5.10.911.0, December 2022cloud service with continuous releases8.0
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercial inforestricted free version is availablecommercialcommercial infofree trial version available
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 languageJava, C++, .NetJavaC++C++
Server operating systemsLinux
OS X
Solaris
Windows
Linux
macOS
Unix
Linux
OS X
Windows
hostedAIX
Linux
Windows
Data schemeyesyesschema-free infoSchema can be enforcedFixed schema with schema-less datatypes (dynamic)yes
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-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.yesnoyesyesno
Secondary indexesyesyes infoalso supports composite index and range indexyesall fields are automatically indexedyes
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLnoyes infoSQL92Kusto Query Language (KQL), SQL subsetyes
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Java API
RESTful HTTP API
TinkerPop Gremlin
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
Groovy
Java
Python
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)asynchronous Gremlin script jobsyes infovia XQuery or JavaScriptYes, possible languages: KQL, Python, Rno
Triggersyes (cache interceptors and events)noyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)yes infodepending on used storage backend, e.g. Cassandra and HBaseyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)via hugegraph-sparkyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infoedges in graphnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infocan act as a resource manager in an XA/JTA transactionno
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.yesyesyes, with Range Indexesnoyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlSecurity Hooks for custom implementationsUsers, roles and permissionsRole-based access control at the document and subdocument levelsAzure Active Directory AuthenticationAccess rights for users, groups and roles according to SQL-standard

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More resources
GridGainHugeGraphMarkLogicMicrosoft Azure Data ExplorerSadas Engine
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