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DBMS > Hazelcast vs. Ignite vs. Kingbase vs. Microsoft Azure Data Explorer vs. Spark SQL

System Properties Comparison Hazelcast vs. Ignite vs. Kingbase vs. Microsoft Azure Data Explorer vs. Spark SQL

Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonIgnite  Xexclude from comparisonKingbase  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA widely adopted in-memory data gridApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.Fully managed big data interactive analytics platformSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeKey-value store
Relational DBMS
Relational DBMSRelational DBMS infocolumn orientedRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Document store
Spatial DBMS
Document 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
Score5.46
Rank#61  Overall
#7  Key-value stores
Score3.11
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score0.50
Rank#257  Overall
#119  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitehazelcast.comignite.apache.orgwww.kingbase.com.cnazure.microsoft.com/­services/­data-explorerspark.apache.org/­sql
Technical documentationhazelcast.org/­imdg/­docsapacheignite.readme.io/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperHazelcastApache Software FoundationBeiJing KINGBASE Information technologies inc.MicrosoftApache Software Foundation
Initial release20082015199920192014
Current release5.3.6, November 2023Apache Ignite 2.6V8.0, August 2021cloud service with continuous releases3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0commercialcommercialOpen Source infoApache 2.0
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 languageJavaC++, Java, .NetC and JavaScala
Server operating systemsAll OS with a Java VMLinux
OS X
Solaris
Windows
Linux
Windows
hostedLinux
OS X
Windows
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 strategyyesyesyesno
Secondary indexesyesyesyesall fields are automatically indexedno
SQL infoSupport of SQLSQL-like query languageANSI-99 for query and DML statements, subset of DDLStandard with numerous extensionsKusto Query Language (KQL), SQL subsetSQL-like DML and DDL statements
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT
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#
C++
Java
PHP
Python
Ruby
Scala
.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor Servicesyes (compute grid and cache interceptors can be used instead)user defined functionsYes, possible languages: KQL, Python, Rno
Triggersyes infoEventsyes (cache interceptors and events)yesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning (by range, list and hash) and vertical partitioningSharding infoImplicit feature of the cloud serviceyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated Mapyes (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 methodsyesyes (compute grid and hadoop accelerator)noSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyImmediate ConsistencyEventual 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 commitedACIDACIDnono
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.yesyesnono
User concepts infoAccess controlRole-based access controlSecurity Hooks for custom implementationsfine grained access rights according to SQL-standardAzure Active Directory Authenticationno

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More resources
HazelcastIgniteKingbaseMicrosoft Azure Data ExplorerSpark SQL
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