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DBMS > GridGain vs. MarkLogic vs. Microsoft Azure Data Explorer vs. Teradata Aster vs. TinkerGraph

System Properties Comparison GridGain vs. MarkLogic vs. Microsoft Azure Data Explorer vs. Teradata Aster vs. TinkerGraph

Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonMarkLogic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTeradata Aster  Xexclude from comparisonTinkerGraph  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteOperational and transactional Enterprise NoSQL databaseFully managed big data interactive analytics platformPlatform for big data analytics on multistructured data sources and typesA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API
Primary database modelKey-value store
Relational DBMS
Document store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMS infocolumn orientedRelational DBMSGraph 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
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
Score0.13
Rank#345  Overall
#35  Graph DBMS
Websitewww.gridgain.comwww.progress.com/­marklogicazure.microsoft.com/­services/­data-explorertinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlin
Technical documentationwww.gridgain.com/­docs/­index.htmlwww.progress.com/­marklogic/­documentationdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperGridGain Systems, Inc.MarkLogic Corp.MicrosoftTeradata
Initial release20072001201920052009
Current releaseGridGain 8.5.111.0, December 2022cloud service with continuous releases
License infoCommercial or Open Sourcecommercialcommercial inforestricted free version is availablecommercialcommercialOpen Source infoApache 2.0
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 languageJava, C++, .NetC++Java
Server operating systemsLinux
OS X
Solaris
Windows
Linux
OS X
Windows
hostedLinux
Data schemeyesschema-free infoSchema can be enforcedFixed schema with schema-less datatypes (dynamic)Flexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeschema-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-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.yesyesyesyes infoin Aster File Storeno
Secondary indexesyesyesall fields are automatically indexedyesno
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLyes infoSQL92Kusto Query Language (KQL), SQL subsetyesno
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
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
ADO.NET
JDBC
ODBC
OLE DB
TinkerPop 3
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C#
C++
Java
Python
R
Groovy
Java
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)yes infovia XQuery or JavaScriptYes, possible languages: KQL, Python, RR packagesno
Triggersyes (cache interceptors and events)yesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)yesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)yes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyes infoSQL Map-Reduce Frameworkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configurationnone
Foreign keys infoReferential integritynonononoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infocan act as a resource manager in an XA/JTA transactionnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesno
Durability infoSupport for making data persistentyesyesyesyesoptional
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes, with Range Indexesnonoyes
User concepts infoAccess controlSecurity Hooks for custom implementationsRole-based access control at the document and subdocument levelsAzure Active Directory Authenticationfine grained access rights according to SQL-standardno

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More resources
GridGainMarkLogicMicrosoft Azure Data ExplorerTeradata AsterTinkerGraph
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