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DBMS > Geode vs. GridGain vs. MarkLogic vs. Microsoft Azure Data Explorer vs. STSdb

System Properties Comparison Geode vs. GridGain vs. MarkLogic vs. Microsoft Azure Data Explorer vs. STSdb

Editorial information provided by DB-Engines
NameGeode  Xexclude from comparisonGridGain  Xexclude from comparisonMarkLogic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesGridGain is an in-memory computing platform, built on Apache IgniteOperational and transactional Enterprise NoSQL databaseFully managed big data interactive analytics platformKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelKey-value storeKey-value store
Relational DBMS
Document store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMS infocolumn orientedKey-value 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
Score1.92
Rank#131  Overall
#23  Key-value stores
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Websitegeode.apache.orgwww.gridgain.comwww.marklogic.comazure.microsoft.com/­services/­data-explorergithub.com/­STSSoft/­STSdb4
Technical documentationgeode.apache.org/­docswww.gridgain.com/­docs/­index.htmldocs.marklogic.comdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.GridGain Systems, Inc.MarkLogic Corp.MicrosoftSTS Soft SC
Initial release20022007200120192011
Current release1.1, February 2017GridGain 8.5.111.0, December 2022cloud service with continuous releases4.0.8, September 2015
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses available as Gemfirecommercialcommercial inforestricted free version is availablecommercialOpen Source infoGPLv2, commercial license 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 languageJavaJava, C++, .NetC++C#
Server operating systemsAll OS with a Java VM infothe JDK (8 or later) is also requiredLinux
OS X
Solaris
Windows
Linux
OS X
Windows
hostedWindows
Data schemeschema-freeyesschema-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 infoprimitive types and user defined types (classes)
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.noyesyesyes
Secondary indexesnoyesyesall fields are automatically indexedno
SQL infoSupport of SQLSQL-like query language (OQL)ANSI-99 for query and DML statements, subset of DDLyes infoSQL92Kusto Query Language (KQL), SQL subsetno
APIs and other access methodsJava Client API
Memcached protocol
RESTful HTTP API
HDFS 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
.NET Client API
Supported programming languages.Net
All JVM based languages
C++
Groovy
Java
Scala
C#
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#
Java
Server-side scripts infoStored proceduresuser defined functionsyes (compute grid and cache interceptors can be used instead)yes infovia XQuery or JavaScriptYes, possible languages: KQL, Python, Rno
Triggersyes infoCache Event Listenersyes (cache interceptors and events)yesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyes (replicated cache)yesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (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-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes, on a single nodeACIDACID infocan act as a resource manager in an XA/JTA transactionnono
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 Indexesno
User concepts infoAccess controlAccess rights per client and object definableSecurity Hooks for custom implementationsRole-based access control at the document and subdocument levelsAzure Active Directory Authenticationno

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More resources
GeodeGridGainMarkLogicMicrosoft Azure Data ExplorerSTSdb
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