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DBMS > Hazelcast vs. Hypertable vs. Informix vs. Linter vs. Microsoft Azure Data Explorer

System Properties Comparison Hazelcast vs. Hypertable vs. Informix vs. Linter vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonHypertable  Xexclude from comparisonInformix  Xexclude from comparisonLinter  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionA widely adopted in-memory data gridAn open source BigTable implementation based on distributed file systems such as HadoopA secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things dataRDBMS for high security requirementsFully managed big data interactive analytics platform
Primary database modelKey-value storeWide column storeRelational DBMS infoSince Version 12.10 support for JSON/BSON datatypes compatible with MongoDBRelational DBMSRelational DBMS infocolumn oriented
Secondary database modelsDocument store infoJSON support with IMDG 3.12Document store
Spatial DBMS
Time Series DBMS infowith Informix TimeSeries Extension
Spatial 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
Score17.87
Rank#35  Overall
#22  Relational DBMS
Score0.09
Rank#346  Overall
#152  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitehazelcast.comwww.ibm.com/­products/­informixlinter.ruazure.microsoft.com/­services/­data-explorer
Technical documentationhazelcast.org/­imdg/­docsinformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
docs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperHazelcastHypertable Inc.IBM, HCL Technologies infoEffective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.relex.ruMicrosoft
Initial release20082009198419902019
Current release5.3.6, November 20230.9.8.11, March 201614.10.FC5, November 2020cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoGNU version 3. Commercial license availablecommercial infofree developer edition availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C, C++ and JavaC and C++
Server operating systemsAll OS with a Java VMLinux
OS X
Windows infoan inofficial Windows port is available
AIX
HP-UX
Linux
macOS
Solaris
Windows
AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
hosted
Data schemeschema-freeschema-freeyesyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesnoyes infoSince Version 12.10 support for JSON/BSON datatypesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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 strategynoyes
Secondary indexesyesrestricted infoonly exact value or prefix value scansyesyesall fields are automatically indexed
SQL infoSupport of SQLSQL-like query languagenoyesyesKusto Query Language (KQL), SQL subset
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
C++ API
Thrift
JDBC
JSON API infoMongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++
Java
Perl
PHP
Python
Ruby
.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor Servicesnoyesyes infoproprietary syntax with the possibility to convert from PL/SQLYes, possible languages: KQL, Python, R
Triggersyes infoEventsnoyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated Mapselectable replication factor on file system levelMulti-source replication
Source-replica replication
Source-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnonoSpark 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 ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitednoACIDACIDno
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.yesyesno
User concepts infoAccess controlRole-based access controlnoUsers with fine-grained authentication, authorization, and auditing controlsfine grained access rights according to SQL-standardAzure Active Directory Authentication

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More resources
HazelcastHypertableInformixLinterMicrosoft Azure Data Explorer
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