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

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

Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonHive  Xexclude from comparisonIngres  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTDSQL for MySQL  Xexclude from comparison
DescriptionA widely adopted in-memory data griddata warehouse software for querying and managing large distributed datasets, built on HadoopWell established RDBMSFully 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 DBMSRelational 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
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score3.80
Rank#82  Overall
#44  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.85
Rank#207  Overall
#97  Relational DBMS
Websitehazelcast.comhive.apache.orgwww.actian.com/­databases/­ingresazure.microsoft.com/­services/­data-explorerwww.tencentcloud.com/­products/­dcdb
Technical documentationhazelcast.org/­imdg/­docscwiki.apache.org/­confluence/­display/­Hive/­Homedocs.actian.com/­ingresdocs.microsoft.com/­en-us/­azure/­data-explorerwww.tencentcloud.com/­document/­product/­1042
DeveloperHazelcastApache Software Foundation infoinitially developed by FacebookActian CorporationMicrosoftTencent
Initial release200820121974 infooriginally developed at University Berkely in early 1970s20192013
Current release5.3.6, November 20233.1.3, April 202211.2, May 2022cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache Version 2commercialcommercialcommercial
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 languageJavaJavaC
Server operating systemsAll OS with a Java VMAll OS with a Java VMAIX
HP Open VMS
HP-UX
Linux
Solaris
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 availableyesno
Secondary indexesyesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statementsyesKusto Query Language (KQL), SQL subsetyes
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
Thrift
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
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
C++
Java
PHP
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 Servicesyes infouser defined functions and integration of map-reduceyesYes, possible languages: KQL, Python, Ryes
Triggersyes infoEventsnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding infoImplicit feature of the cloud serviceAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated Mapselectable replication factorIngres Replicatoryes 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 methodsyesyes infoquery execution via MapReducenoSpark 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 AlgorithmEventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitednoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCCyesyes
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.yesnonono
User concepts infoAccess controlRole-based access controlAccess rights for users, groups and rolesfine grained access rights according to SQL-standardAzure Active Directory AuthenticationUsers with fine-grained authorization concept

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More resources
HazelcastHiveIngresMicrosoft Azure Data ExplorerTDSQL for MySQL
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