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DBMS > GBase vs. Hazelcast vs. Microsoft Azure Data Explorer vs. MonetDB vs. Sqrrl

System Properties Comparison GBase vs. Hazelcast vs. Microsoft Azure Data Explorer vs. MonetDB vs. Sqrrl

Editorial information provided by DB-Engines
NameGBase  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMonetDB  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionAn analytical database for business intelligence with large customers in China.A widely adopted in-memory data gridFully managed big data interactive analytics platformA relational database management system that stores data in columnsAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelRelational DBMSKey-value storeRelational DBMS infocolumn orientedRelational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
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)
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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.81
Rank#166  Overall
#80  Relational DBMS
Score9.16
Rank#44  Overall
#5  Key-value stores
Score2.75
Rank#89  Overall
#45  Relational DBMS
Score1.60
Rank#123  Overall
#60  Relational DBMS
Websitewww.gbase8a.comhazelcast.comazure.microsoft.com/­services/­data-explorerwww.monetdb.orgsqrrl.com
Technical documentationhazelcast.org/­documentationdocs.microsoft.com/­en-us/­azure/­data-explorerwww.monetdb.org/­Documentation
DeveloperHazelcastMicrosoftMonetDB BVAmazon infooriginally Sqrrl Data, Inc.
Initial release2008201920042012
Current releaseGBase 8a4.0, February 2020cloud service with continuous releasesNov2019-SP1, December 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoMozilla Public License 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
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 VMhostedFreeBSD
Linux
OS X
Solaris
Windows
Linux
Data schemeschema-freeFixed schema with schema-less datatypes (dynamic)yesschema-free
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes
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 strategyyes
Secondary indexesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLSQL-like query languageKusto Query Language (KQL), SQL subsetyes infoSQL 2003 with some extensionsno
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor ServicesYes, possible languages: KQL, Python, Ryes, in SQL, C, Rno
Triggersyes infoEventsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceSharding via remote tablesSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated Mapyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none infoMaster-slave replication available in experimental statusselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate Consistency
Immediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitednoACIDAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlRole-based access controlAzure Active Directory Authenticationfine grained access rights according to SQL-standardCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)
More information provided by the system vendor
GBaseHazelcastMicrosoft Azure Data ExplorerMonetDBSqrrl
Specific characteristicsHazelcast is an in-memory computing platform that runs applications with extremely...
» more
Azure Data Explorer is a fast and highly scalable data exploration service for log...
» more
Column-store In-memory optimized GeoSpatial support JSON document support
» more
Competitive advantagesHazelcast has an optimized, multi-threaded architecture that enables the highest...
» more
Kusto Query Language (innovative query language, optimized for high performance data...
» more
Scalable architecture - vertical data organization and in-memory optimization guarantee...
» more
Typical application scenariosHazelcast powers many types of large-scale, data processing applications. A sample...
» more
IoT applications IoT devices generate billions of sensor readings. Normalizing and...
» more
Analytical database, Data warehouse, OLAP Data mining Scientific database
» more
Key customersHazelcast customers include 50 of the world’s largest financial services companies,...
» more
Microsoft, DocuSign, Taboola, Bosch, Siemens Healthineers, Bühler, Ecolab, Zoomd
» more
Numascale , Spinque , SecurActive , CHS , NOZHUP
» more
Market metricsAzure Data Explorer is the data service for Azure Monitor, Azure Time Series Insights,...
» more
Licensing and pricing modelsHazelcast provides both open source and commercial software. The open source offering...
» more
Free and open-source software, Mozilla Public License 2.0 Commercial support available
» more
News

Optimistic Concurrency Control in MonetDB
3 January 2020

Limit memory usage of MonetDB on Linux with CGROUPS
9 May 2019

SQL:2003 merge statements now supported in MonetDB
8 March 2019

Extended SQL:2011 Window Functions in MonetDB
26 February 2019

Updatable MERGE TABLEs with partition predicates
26 February 2019

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
GBaseHazelcastMicrosoft Azure Data ExplorerMonetDBSqrrl
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