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DBMS > Hazelcast vs. Ignite vs. Linter vs. Microsoft Azure Data Explorer vs. VoltDB

System Properties Comparison Hazelcast vs. Ignite vs. Linter vs. Microsoft Azure Data Explorer vs. VoltDB

Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonIgnite  Xexclude from comparisonLinter  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonVoltDB  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.RDBMS for high security requirementsFully managed big data interactive analytics platformDistributed In-Memory NewSQL RDBMS infoUsed for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory
Primary database modelKey-value storeKey-value store
Relational DBMS
Relational DBMSRelational DBMS infocolumn orientedRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Spatial DBMSDocument 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
Score5.97
Rank#57  Overall
#6  Key-value stores
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score0.09
Rank#346  Overall
#152  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score1.44
Rank#158  Overall
#73  Relational DBMS
Websitehazelcast.comignite.apache.orglinter.ruazure.microsoft.com/­services/­data-explorerwww.voltdb.com
Technical documentationhazelcast.org/­imdg/­docsapacheignite.readme.io/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.voltdb.com
DeveloperHazelcastApache Software Foundationrelex.ruMicrosoftVoltDB Inc.
Initial release20082015199020192010
Current release5.3.6, November 2023Apache Ignite 2.6cloud service with continuous releases11.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0commercialcommercialOpen Source infoAGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions
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 C++Java, C++
Server operating systemsAll OS with a Java VMLinux
OS X
Solaris
Windows
AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
hostedLinux
OS X infofor development
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 strategyyesnoyes
Secondary indexesyesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query languageANSI-99 for query and DML statements, subset of DDLyesKusto Query Language (KQL), SQL subsetyes infoonly a subset of SQL 99
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
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Java API
JDBC
RESTful HTTP/JSON API
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C#
C++
Erlang infonot officially supported
Go
Java
JavaScript infoNode.js
PHP
Python
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor Servicesyes (compute grid and cache interceptors can be used instead)yes infoproprietary syntax with the possibility to convert from PL/SQLYes, possible languages: KQL, Python, RJava
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 nodesShardingShardingnoneSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated Mapyes (replicated cache)Source-replica replicationyes 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 (compute grid and hadoop accelerator)noSpark 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 ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesnono infoFOREIGN KEY constraints are not supported
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitedACIDACIDnoACID infoTransactions are executed single-threaded within stored procedures
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infoData access is serialized by the server
Durability infoSupport for making data persistentyesyesyesyesyes infoSnapshots and command logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlRole-based access controlSecurity Hooks for custom implementationsfine grained access rights according to SQL-standardAzure Active Directory AuthenticationUsers and roles with access to stored procedures

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More resources
HazelcastIgniteLinterMicrosoft Azure Data ExplorerVoltDB
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