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DBMS > GridGain vs. JaguarDB vs. Microsoft Azure Data Explorer vs. Titan

System Properties Comparison GridGain vs. JaguarDB vs. Microsoft Azure Data Explorer vs. Titan

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Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonJaguarDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTitan  Xexclude from comparison
Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.
DescriptionGridGain is an in-memory computing platform, built on Apache IgnitePerformant, highly scalable DBMS for AI and IoT applicationsFully managed big data interactive analytics platformTitan is a Graph DBMS optimized for distributed clusters.
Primary database modelKey-value store
Relational DBMS
Key-value store
Vector DBMS
Relational DBMS infocolumn orientedGraph 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
Score0.06
Rank#381  Overall
#59  Key-value stores
#14  Vector DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websitewww.gridgain.comwww.jaguardb.comazure.microsoft.com/­services/­data-explorergithub.com/­thinkaurelius/­titan
Technical documentationwww.gridgain.com/­docs/­index.htmlwww.jaguardb.com/­support.htmldocs.microsoft.com/­en-us/­azure/­data-explorergithub.com/­thinkaurelius/­titan/­wiki
DeveloperGridGain Systems, Inc.DataJaguar, Inc.MicrosoftAurelius, owned by DataStax
Initial release2007201520192012
Current releaseGridGain 8.5.13.3 July 2023cloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoGPL V3.0commercialOpen Source infoApache license, version 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetC++ infothe server part. Clients available in other languagesJava
Server operating systemsLinux
OS X
Solaris
Windows
LinuxhostedLinux
OS X
Unix
Windows
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)yes
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-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.yesnoyes
Secondary indexesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLA subset of ANSI SQL is implemented infobut no views, foreign keys, triggersKusto Query Language (KQL), SQL subsetno
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Clojure
Java
Python
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)noYes, possible languages: KQL, Python, Ryes
Triggersyes (cache interceptors and events)noyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceyes infovia pluggable storage backends
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)Multi-source replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)noSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyes infovia Faunus, a graph analytics engine
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyes infoRelationships in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlSecurity Hooks for custom implementationsrights management via user accountsAzure Active Directory AuthenticationUser authentification and security via Rexster Graph Server

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More resources
GridGainJaguarDBMicrosoft Azure Data ExplorerTitan
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