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DBMS > GigaSpaces vs. Kdb vs. Microsoft Azure Data Explorer vs. RDF4J vs. Sequoiadb

System Properties Comparison GigaSpaces vs. Kdb vs. Microsoft Azure Data Explorer vs. RDF4J vs. Sequoiadb

Editorial information provided by DB-Engines
NameGigaSpaces  Xexclude from comparisonKdb  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSequoiadb  Xexclude from comparison
DescriptionHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsHigh performance Time Series DBMSFully managed big data interactive analytics platformRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.NewSQL database with distributed OLTP and SQL
Primary database modelDocument store
Object oriented DBMS infoValues are user defined objects
Time Series DBMS
Vector DBMS
Relational DBMS infocolumn orientedRDF storeDocument store
Relational DBMS
Secondary database modelsGraph DBMS
Search engine
Relational 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
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Websitewww.gigaspaces.comkx.comazure.microsoft.com/­services/­data-explorerrdf4j.orgwww.sequoiadb.com
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmlcode.kx.comdocs.microsoft.com/­en-us/­azure/­data-explorerrdf4j.org/­documentationwww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperGigaspaces TechnologiesKx Systems, a division of First Derivatives plcMicrosoftSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Sequoiadb Ltd.
Initial release20002000 infokdb was released 2000, kdb+ in 2003201920042013
Current release15.5, September 20203.6, May 2018cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial licenses availablecommercial infofree 32-bit versioncommercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoServer: AGPL; Client: Apache V2
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetqJavaC++
Server operating systemsLinux
macOS
Solaris
Windows
Linux
OS X
Solaris
Windows
hostedLinux
OS X
Unix
Windows
Linux
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)yes infoRDF Schemasschema-free
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes infooid, date, timestamp, binary, regex
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.no infoXML can be used for describing objects metadatayesyesno
Secondary indexesyesyes infotable attribute 'grouped'all fields are automatically indexedyesyes
SQL infoSupport of SQLSQL-99 for query and DML statementsSQL-like query language (q)Kusto Query Language (KQL), SQL subsetnoSQL-like query language
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
proprietary protocol using JSON
Supported programming languages.Net
C++
Java
Python
Scala
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
PHP
Python
.Net
C++
Java
PHP
Python
Server-side scripts infoStored proceduresyesuser defined functionsYes, possible languages: KQL, Python, RyesJavaScript
Triggersyes, event driven architectureyes infowith viewsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningSharding infoImplicit feature of the cloud servicenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Source-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsno infosimilar paradigm used for internal processingSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID infoIsolation support depends on the API usedDocument is locked during a transaction
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory storage is supported as wellyes
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 controlrights management via user accountsAzure Active Directory Authenticationnosimple password-based access control
More information provided by the system vendor
GigaSpacesKdbMicrosoft Azure Data ExplorerRDF4J infoformerly known as SesameSequoiadb
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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GigaSpacesKdbMicrosoft Azure Data ExplorerRDF4J infoformerly known as SesameSequoiadb
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