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DBMS > Hazelcast vs. Ingres vs. JanusGraph vs. Microsoft Azure Data Explorer vs. TDSQL for MySQL

System Properties Comparison Hazelcast vs. Ingres vs. JanusGraph vs. Microsoft Azure Data Explorer vs. TDSQL for MySQL

Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonIngres  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTDSQL for MySQL  Xexclude from comparison
DescriptionA widely adopted in-memory data gridWell established RDBMSA Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017Fully managed big data interactive analytics platformA high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.
Primary database modelKey-value storeRelational DBMSGraph DBMSRelational DBMS infocolumn orientedRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Document 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
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.46
Rank#61  Overall
#7  Key-value stores
Score3.80
Rank#82  Overall
#44  Relational DBMS
Score2.02
Rank#125  Overall
#12  Graph DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.85
Rank#207  Overall
#97  Relational DBMS
Websitehazelcast.comwww.actian.com/­databases/­ingresjanusgraph.orgazure.microsoft.com/­services/­data-explorerwww.tencentcloud.com/­products/­dcdb
Technical documentationhazelcast.org/­imdg/­docsdocs.actian.com/­ingresdocs.janusgraph.orgdocs.microsoft.com/­en-us/­azure/­data-explorerwww.tencentcloud.com/­document/­product/­1042
DeveloperHazelcastActian CorporationLinux Foundation; originally developed as Titan by AureliusMicrosoftTencent
Initial release20081974 infooriginally developed at University Berkely in early 1970s201720192013
Current release5.3.6, November 202311.2, May 20220.6.3, February 2023cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCJava
Server operating systemsAll OS with a Java VMAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Linux
OS X
Unix
Windows
hostedhosted
Data schemeschema-freeyesyesFixed 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.yes infothe object must implement a serialization strategyno infobut tools for importing/exporting data from/to XML-files availablenoyesno
Secondary indexesyesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query languageyesnoKusto Query Language (KQL), SQL subsetyes
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Clojure
Java
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C#
C++
Java
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor ServicesyesyesYes, possible languages: KQL, Python, Ryes
Triggersyes infoEventsyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslyyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)Sharding infoImplicit feature of the cloud serviceAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated MapIngres Replicatoryesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes infovia Faunus, a graph analytics engineSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesyes infoRelationships in graphsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitedACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoMVCCyesyesyes
Durability infoSupport for making data persistentyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonono
User concepts infoAccess controlRole-based access controlfine grained access rights according to SQL-standardUser authentification and security via Rexster Graph ServerAzure Active Directory AuthenticationUsers with fine-grained authorization concept

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More resources
HazelcastIngresJanusGraph infosuccessor of TitanMicrosoft Azure Data ExplorerTDSQL for MySQL
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